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1.	van de Beek, Jan-Jaap, et al. (författare) Three non-pilot based time- and frequency estimators for OFDM 2000 Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 80:7, s. 1321-1334 Tidskriftsartikel (refereegranskat)abstract Time-domain maximum-likelihood (ML) estimators of time and frequency offsets are derived for three orthogonal frequency division multiplexing (OFDM) signal models: a pulse-shaped one-shot OFDM signal, a stream of multiple OFDM signals and an OFDM signal in a dispersive channel environment. We then develop structures to simplify their implementation. Simulation results show the relative performance and strengths of each of these three estimators.
2.	Wahlberg, Patrik, et al. (författare) Methods for alignment of multi-class signal sets 2003 Ingår i: Signal Processing. - 0165-1684. ; 83:5, s. 983-1000 Tidskriftsartikel (refereegranskat)abstract The paper treats jitter estimation for alignment of a set of signals which contains several unknown classes of waveforms. The motivating application is epileptic EEG spikes. where alignment prior to clustering and averaging is desired. The assumption that the signal waveforms are unknown precludes the use of classical techniques, notably matched filtering. Instead we treat two other classes of methods. In the first class the jitter of each signal is estimated with aid of the whole data set, using the Rayleigh quotient of the sample correlation matrix. The main idea of the paper is the suggestion of two such methods, consisting respectively of mean value computation and maximization of the Rayleigh quotient as a function of translation of a given signal. In the second class of methods each signal is processed individually, and one such method is estimation of the jitter of a signal by its centre of gravity. By means of deduction, simulations and evaluation on real life epileptic EEG signals, we show that the first class of methods is preferable to the second. Simulations also show that the method of maximization of the Rayleigh quotient seems to be a generally good method, which gives small estimation error and is applicable in a wide range of circumstances. For seven investigated sets of real life EEG data, the maximization algorithm turned out to give the best results, and improved alignment in the majority of signal clusters. (C) 2003 Elsevier Science B.V. All rights reserved.
3.	Anderson, Sören (författare) On Optimal Dimension Reduction for Sensor Array Signal Processing 1993 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 30:2, s. 245-256 Tidskriftsartikel (refereegranskat)abstract The computational complexity for direction-of-arrival estimation using sensor arrays increases very rapidly with the number of sensors in the array. One way to lower the amount of computations is to employ some kind of reduction of the data dimension. This is usually accomplished by employing linear transformations for mapping full dimension data into a lower dimensional space. Different approaches for selecting these transformations have been proposed. In this paper, a transformation matrix is derived that makes it possible to theoretically attain the full-dimension Cramér-Rao bound also in the reduced space. A bound on the dimension of the reduced data set is given, above which it is always possible to obtain the same accuracy for the estimates of the source localizations, using the lower-dimension data, as that achievable by using the full dimension data. Furthermore, a method is devised for designing the transformation matrix. Numerical examples, using this design method, are presented, where the achievable performance of the (optimal) Weighted Subspace Fitting method with full dimension data is compared to the performance obtained with reduced dimension data. The problem of estimating parameters of sinusoidal signals from noisy data is also addressed by a direct application of the results derived herein.
4.	Carlsson, B, et al. (författare) A NOTCH FILTER BASED ON RECURSIVE LEAST-SQUARES MODELING 1994 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 35:3, s. 231-239 Tidskriftsartikel (refereegranskat)abstract This paper presents a notch filter based on recursive least-squares sinusoidal modelling. This gives analytical insight both into least-squares modelling of sine waves in noise and the use of constrained notch filters. Especially, the derived filter corresponds to a commonly used notch filter with constrained poles and zeros.
5.	Elias, Elizabeth, et al. (författare) Tree-structured IIR/FIR uniform-band and octave-band filter banks with very low-complexity analysis or synthesis filters 2003 Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 83:9, s. 1997-2009 Tidskriftsartikel (refereegranskat)abstract This paper introduces new tree-structured uniform-band and octave-band digital filter banks (FBs). These FBs make use of half-band IIR filters in the analysis FBs and FIR filters in the synthesis FBs. The resulting FBs are asymmetric in the sense that the analysis FB has a very low arithmetic complexity whereas that in the synthesis FB is higher. However, compared with other asymmetric FBs, the proposed ones have in many cases a lower overall arithmetic complexity and delay. The proposed FBs have magnitude distortion but no phase distortion, further, the aliasing components are either zero (uniform-band case) or approximately zero (octave-band case). The FBs are designed using linear and nonlinear programming. Design examples are included demonstrating the properties of the proposed filters banks. ⌐ 2003 Published by Elsevier B.V.
6.	Granlund, Gösta (författare) The Complexity of Vision 1999 Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 74:1, s. 101-126 Tidskriftsartikel (refereegranskat)abstract There is no indication that it will ever be possible to find some simple trick that miraculously solves most problems in vision. It turns out that the processing system must be able to implement a model structure, the complexity of which is directly related to the structural complexity of the problem under consideration in the external world. It has become increasingly apparent that Vision cannot be treated in isolation from the response generation, because a very high degree of integration is required between different levels of percepts and corresponding response primitives. The response to be produced at a given instance is as much dependent upon the state of the system, as the percepts impinging upon the system. In addition, it has become apparent that many classical aspects of perception, such as geometry, probably do not belong to the percept domain of a Vision system, but to the response domain. This article will focus on what are considered crucial problems in Vision for robotics for the future, rather than on the classical solutions today. It will discuss hierarchical architectures for combination of percept and response primitives. It will discuss the concept of combined percept-response invariances as important structural elements for Vision. It will be maintained that learning is essential to obtain the necessary flexibility and adaptivity. In consequence, it will be argued that invariances for the purpose of Vision are not abstractly geometrical, but derived from the percept-response interaction with the environment. The issue of information representation becomes extremely important in distributed structures of the types foreseen, where uncertainty of information has to be stated for update of models and associated data. The question of object representation is central to the paper. Equivalence is established between the representations of response, geometry and time. Finally an integrated percept-response structure is proposed for flexible response control.
7.	Händel, Peter, 1962-, et al. (författare) Asymptotic noise gain of polynomial predictors 1997 Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 62:2, s. 247-250 Tidskriftsartikel (refereegranskat)abstract Finite impulse response filters for the prediction of polynomial signals are considered. An expression for the asymptotic noise gain (as the filter length increases without bound) is derived. It is shown that the asymptotic noise gain only depends on the polynomial order - in particular, it is independent of the prediction horizon. It is also shown that the noise gain forms a non-increasing sequence for increasing filter lengths. Numerical results that lend support to the theoretical findings are included.
8.	Händel, Peter, 1962-, et al. (författare) Asymptotic variance of the AR spectral estimator for noisy sinusoidal data 1994 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 35:2, s. 131-139 Tidskriftsartikel (refereegranskat)abstract In this paper the autoregressive (AR) spectral estimator is analyzed in the case of noisy sinusoidal data. An expression for the large-sample normalized variance is derived and studied in detail for increasing model order. In particular, a very simple formula is derived for the asymptotic (in both number of observed data and model order) normalized variance, which confirms a conjecture made by Sakai.
9.	Händel, Peter, 1962- (författare) High-order Yule-Walker estimation of the parameters of exponentially damped cisoids in noise 1993 Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 32:3, s. 315-328 Tidskriftsartikel (refereegranskat)abstract An approach for the estimation of the frequencies and damping factors of exponentially damped cisoids (complex sinusoids) is presented. The method may be seen as an extension of the method of backward linear prediction and singular value decomposition of Kumaresan and Tufts to the second-order statistics domain. The proposed estimator is interpreted as a high-order Yule-Walker (HOYW) method using a data based covariance matrix. The HOYW method is analysed at high SNR where closed-form expressions for the accuracy of the estimates are derived. By Monte Carlo simulations the HOYW method is applied to data consisting of one and two damped cisoids in additive white noise. The simulation results are compared with the results using the Kumaresan and Tufts method, with the Cramer-Rao bound, and with the derived theoretical results. The method is not statistically efficient, but the comparison shows that the HOYW method outperforms the method of Kumaresan and Tufts in terms of accuracy versus algorithmic complexity and in terms of precision in the cases considered. Due to the above properties the method is suitable to provide fast initial estimates for nonlinear search methods.
10.	Händel, Peter, 1962-, et al. (författare) Performance analysis of a correlation based single tone frequency estimator 1995 Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 44:2, s. 223-231 Tidskriftsartikel (refereegranskat)abstract This paper analyzes the frequency error variance of a low complexity single tone frequency estimator based on sample correlations of the input data. In the high SNR scenario it is analytically shown that the accuracy of a properly tuned algorithm is nearly optimal, i.e. nearly attains the Cramer-Rao lower bound. For low SNR the statistical efficiency of the algorithm is degraded, but it is analytically proven that for a large number of samples the error variance attains the lower bound for this class of estimators.
11.	Isaksson, Alf, et al. (författare) Inverse Glottal Filtering using a Parameterized Input Model 1989 Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 18:4, s. 435-445 Tidskriftsartikel (refereegranskat)abstract In this paper computational algorithms for inverse glottal filtering are studied. The objective of inverse glottal filtering is to estimate the driving source. A good model for the glottal pulse is useful for, e.g., speech synthesis, speech recognition and speaker diagnostics. One common approach is to use a parameterized model of the input signal, i.e., the glottal pulses. The algorithm presented enables simultaneous estimation of the parameters of the input signal and the parameters of the system transfer function, the vocal tract model. The presentation here is restricted to transfer functions of all-pole type, i.e., AR-models. The method can be extended to handle zeros in the transfer function. The computational burden would, however, increase significantly. The algorithm uses efficient numerical methods, as, for instance, QR-factorization through Householder transformations.
12.	Jansson, Magnus, et al. (författare) A Linear Regression Approach to State-Space Subspace System Identification 1996 Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 52:2, s. 103-129 Tidskriftsartikel (refereegranskat)abstract Recently, state-space subspace system identification (4SID) has been suggested as an alternative to the more traditional prediction error system identification. The aim of this paper is to analyze the connections between these two different approaches to system identification. The conclusion is that 4SID can be viewed as a linear regression multistep-ahead prediction error method with certain rank constraints. This allows us to describe 4SID methods within the standard framework of system identification and linear regression estimation. For example, this observation is used to compare different cost-functions which occur rather implicitly in the ordinary framework of 4SID. From the cost-functions, estimates of the extended observability matrix are derived and related to previous work. Based on the estimates of the observability matrix, the asymptotic properties of two pole estimators, namely the shift invariance method and a weighted subspace fitting method, are analyzed. Expressions for the asymptotic variances of the pole estimation error are given. From these expressions, difficulties in choosing user-specified parameters are pointed out. Furthermore, it is found that a row-weighting in the subspace estimation step does not affect the pole estimation error asymptotically.
13.	Jansson, Magnus, et al. (författare) Forward-Only and Forward-Backward Sample Covariances – A Comparative Study 1999 Ingår i: Signal Processing. - 0165-1684. ; 77:3, s. 235-245 Tidskriftsartikel (refereegranskat)abstract In some applications the covariance matrix of the observations enjoys a particular symmetry: it is not only symmetric with respect to its main diagonal but also with respect to the anti-diagonal. The standard forward-only sample covariance estimate does not impose this extra symmetry. In such cases one often uses the so-called forward-backward sample covariance estimate. In this paper, a direct comparative study of the relative accuracy of the two sample covariance estimates is performed. An explicit expression for the difference between the estimation error covariance matrices of the two sample covariance estimates is given. This expression shows quantitatively the gain of using the forward-backward estimate compared to the forward-only estimate. The presented results are also useful in the analysis of estimators based on either of the two sample covariances. As an example, spatial power estimation by means of the Capon method is considered. Using a second-order approximation, it is shown that Capon based on the forward-only sample covariance (F-Capon) underestimates the power spectrum, and also that the bias for Capon based on the forward-backward sample covariance is half that of F-Capon.
14.	Koeck, Philip J B (författare) Quantization errors in averaged digitized data 2001 Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 81:2, s. 345-356 Tidskriftsartikel (refereegranskat)abstract Analytic expressions which describe average quantization errors in digitized data with additive noise are derived. The magnitude of this error depends on the noise present in the analog signal, the bin-size (the difference between neighboring quantization levels) and also the signal itself. An iterative process, which corrects for these residual quantization errors after averaging, is proposed and tested in simulations. Alternatively a method for avoiding quantization errors during digitization of signals which will later be averaged is suggested.
15.	Kristensson, Martin, et al. (författare) Modified IQML and Weighted Subspace Fitting without Eigendecomposition 1999 Ingår i: Signal Processing. - : Elsevier North-Holland, Inc. Amsterdam, The Netherlands. - 0165-1684. ; 79:1, s. 29-44 Tidskriftsartikel (refereegranskat)abstract This paper deals with direction estimation of signals impinging on a uniform linear sensor array. A well-known algorithm for this problem is IQML. However, estimates computed with IQML are in general biased, especially in noisy scenarios. We propose a modification of IQML (MIQML) that gives consistent estimates at approximately the same computational cost. In addition, an algorithm (WSF-E) with an estimation error covariance which is asymptotically identical to the asymptotic Cramér–Rao lower bound is presented. The WSF-E algorithm resembles weighted subspace fitting (WSF) or MODE, but achieves optimal performance without having to compute an eigendecomposition of the sample covariance matrix.
16.	Larsson, Erik G., et al. (författare) Spectral estimation via adaptive filterbank methods : a unified analysis and a new algorithm 2002 Ingår i: Signal Processing. - Amsterdam, The Netherlands : Elsevier. - 0165-1684 .- 1872-7557. ; 82:12, s. 1991-2001 Tidskriftsartikel (refereegranskat)abstract The problem of estimating the amplitude spectrum of a signal is of interest in a number of applications ranging from radar imaging to time-series analysis. The so-called adaptive filterbank-based nonparametric spectral estimators have recently received renewed interest as potential solutions to this problem. In essence, the adaptive filterbank methods determine an estimate of the spectrum for a frequency of interest by computing a finite impulse response filter according to a certain criterion and fitting a sinusoid to the filtered data sequence. In this paper, we first analyze the asymptotic estimation accuracy of the amplitude spectrum for various filterbank estimators. Next, we propose a new adaptive filterbank estimator based on a minimum mean square error criterion. Numerical examples indicate that the new estimator can have a better resolution capability than previously known filterbank estimators.
17.	Ljung, Lennart, 1946- (författare) Aspects on the System Identification Problem 1982 Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 4:5-6, s. 445-456 Tidskriftsartikel (refereegranskat)abstract System Identification concerns the problem of building mathematical models of a dynamical system from measured input-output data. In this paper we examine some aspects of this problem. Typical sets of models are displayed and basic principles for fitting them to data are discussed. Asymptotic properties of the resulting model are also quoted.
18.	Ljung, Lennart, 1946-, et al. (författare) Subspace Identification from Closed Loop Data 1996 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 52:2, s. 209-215 Tidskriftsartikel (refereegranskat)abstract The so-called subspace methods for direct identification of linear models in state space form have drawn considerable interest recently. They have been found to work well in many cases but have one drawback — they do not yield consistent estimates for data collected under output feedback. The present paper points to the reasons for this. We stress how the basic idea is to focus on the estimation of the state-variable candidates — the k-step ahead output predictors. By recomputing these from a ‘non-parametric’ (or, rather, high order ARX) one-step ahead predictor model, closed loop data can be handled.
19.	Stoica, Petre, et al. (författare) The evil of superefficiency 1996 Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 55:1, s. 133-136 Tidskriftsartikel (refereegranskat)abstract We discuss the intriguing notion of statistical superefficiency in a straightforward manner with a minimum of formality. We point out that for any given parameter estimator there exist other estimators which have a strictly lower asymptotic variance and hence are statistically more efficient than the former. In particular, if the former estimator was statistically efficient (in the sense that its asymptotic variance was equal to the Cramer-Rao bound) then the latter estimators could be called ''superefficient''. Among others, the phenomenon of superefficiency implies that asymptotically there exists no uniformly minimum-variance parameter estimator.
20.	Tichavsky, P., et al. (författare) Recursive estimation of frequencies and frequency rates of multiple cisoids in noise 1997 Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 58:2, s. 117-129 Tidskriftsartikel (refereegranskat)abstract A recursive algorithm for simultaneous estimation and tracking of instantaneous frequencies and instantaneous frequency rates-of-change for signals that consist of multiple narrow-band components in noise is proposed and studied. The algorithm recursively separates the signal to individual components and uses estimated phase differences for updating the instantaneous frequency and frequency rate of each component. The main advantages of the proposed algorithm over frequencies-only tracking algorithms known in literature include the zero asymptotic bias (zero tracking delay) in estimating of the instantaneous frequencies of linear FM (chirp) signals and more accurate tracking of frequencies that cross each other. Performance of the algorithm is studied by means of a linear filter approximation technique and derived results are compared with the appropriate (posterior) Cramer-Rao bound. Superior performance of the algorithm is illustrated by computer simulations.
21.	Trump, Tõnu, et al. (författare) Estimation of Nominal Direction of Arrival and Angular Spread Using an Array of Sensors 1996 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 50:1-2, s. 57-69 Tidskriftsartikel (refereegranskat)abstract The problem of estimating the nominal direction of arrival and angular spread of a source surrounded by a large number of local scatterers using an array of sensors is addressed. This type of propagation occurs frequently in, for example, mobile communications. The maximum likelihood estimator is considered and two computationally less complex estimators are also proposed. They are based on least-squares fits of the sample covariance to the theoretical covariance matrix derived from the measurement model. The performance of the least-squares-based algorithm is analyzed and based on this, an optimally weighted least-squares criterion is proposed. The weighted least-squares algorithm is shown to be asymptotically efficient. Results of numerical experiments are presented to indicate small sample behavior of the estimators. The nominal direction-of-arrival (DOA) estimates are compared with those provided by a standard subspace algorithm. Finally, the methods are applied to experimental array data to determine spread angles for non line of sight scenarios.
22.	Viberg, Mats (författare) Sensitivity of Parametric Direction Finding to Colored Noise Fields and Undermodeling 1993 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 34:2, s. 207-222 Tidskriftsartikel (refereegranskat)abstract A fundamental assumption for most direction finding algorithms is that the spatial correlation structure of the background noise (i.e., the correlation from sensor to sensor) is known to within a multiplicative scalar. In practive, this is often achieved by measuring the array covariance when no signals are present, a procedure which is unavoidably subjected to errors. The presence of undetected weak signals gives rise to similar perturbations. In this paper, the effect of such modeling errors on parametric estimation techniques is examined. First-order expressions for the mean square error (MSE) of the parameter estimates are derived for the deterministic and stochastic maximum likelihood methods and the weighted subspace fitting technique. The spatial noise correlation structures that lead to maximum performance loss are identified under different assumptions. In case of high signal-to-noise ratio, it is found that the MSE can be increased by a factor equal to the number of sensors in the array, as compared to spatially white noise. Furthermore, it is demonstrated that the presence of a relatively weak (− 15 dB) undetected signal can result in a large bias (≈1°) on the estimates of the other signal directions.
23.	Wigren, Torbjörn (författare) Avoiding ill-convergence of finite dimensional blind adaptation schemes excited by discrete symbol sequences 1997 Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 62:2, s. 121-162 Tidskriftsartikel (refereegranskat)
24.	Adalbjörnsson, Stefan Ingi, et al. (författare) Multi-Pitch Estimation Exploiting Block Sparsity 2015 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 109:April, s. 236-247 Tidskriftsartikel (refereegranskat)abstract We study the problem of estimating the fundamental frequencies of a signal containing multiple harmonically related sinusoidal components using a novel block sparse signal representation. An efficient algorithm for solving the resulting optimization problem is devised exploiting a novel variable step-size alternating direction method of multipliers (ADMM). The resulting algorithm has guaranteed convergence and shows notable robustness to the f 0 vs f0/2f0/2 ambiguity problem. The superiority of the proposed method, as compared to earlier presented estimation techniques, is demonstrated using both simulated and measured audio signals, clearly indicating the preferable performance of the proposed technique.
25.	Ambat, Sooraj K., et al. (författare) Progressive fusion of reconstruction algorithms for low latency applications in compressed sensing 2014 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 97, s. 146-151 Tidskriftsartikel (refereegranskat)abstract Recently, it has been shown that fusion of the estimates of a set of sparse recovery algorithms result in an estimate better than the best estimate in the set, especially when the number of measurements is very limited. Though these schemes provide better sparse signal recovery performance, the higher computational requirement makes it less attractive for low latency applications. To alleviate this drawback, in this paper, we develop a progressive fusion based scheme for low latency applications in compressed sensing. In progressive fusion, the estimates of the participating algorithms are fused progressively according to the availability of estimates. The availability of estimates depends on computational complexity of the participating algorithms, in turn on their latency requirement. Unlike the other fusion algorithms, the proposed progressive fusion algorithm provides quick interim results and successive refinements during the fusion process, which is highly desirable in low latency applications. We analyse the developed scheme by providing sufficient conditions for improvement of CS reconstruction quality and show the practical efficacy by numerical experiments using synthetic and real-world data.
26.	Andersson, Kenneth, 1970-, et al. (författare) Prediction from off-grid samples using continuous normalized convolution 2007 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 87:3, s. 353-365 Tidskriftsartikel (refereegranskat)abstract This paper presents a novel method for performing fast estimation of data samples on a desired output grid from samples on an irregularly sampled grid. The output signal is estimated using integration of signals over a neighbourhood employing a local model of the signal using discrete filters. The strength of the method is demonstrated in motion compensation examples by comparing to traditional techniques.
27.	Angelopoulos, Kostas, et al. (författare) Computationally Efficient Sparsity-Inducing Coherence Spectrum Estimation of Complete and Non-Complete Data Sets 2013 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 93:5, s. 1221-1234 Tidskriftsartikel (refereegranskat)abstract The magnitude squared coherence (MSC) spectrum is an often used frequency-dependent measure for the linear dependency between two stationary processes, and the recent literature contain several contributions on how to form high-resolution data-dependent and adaptive MSC estimators, and on the efficient implementation of such estimators. In this work, we further this development with the presentation of computationally efficient implementations of the recent iterative adaptive approach (IAA) estimator, present a novel sparse learning via iterative minimization (SLIM) algorithm, discuss extensions to two-dimensional data sets, examining both the case of complete data sets and when some of the observations are missing. The algorithms further the recent development of exploiting the estimators' inherently low displacement rank of the necessary products of Toeplitz-like matrices, extending these formulations to the coherence estimation using IAA and SLIM formulations. The performance of the proposed algorithms and implementations are illustrated both with theoretical complexity measures and with numerical simulations.
28.	Azizzadeh, Azad, et al. (författare) BER performance analysis of coarsely quantized uplink massive MIMO 2019 Ingår i: Signal Processing. - : ELSEVIER. - 0165-1684 .- 1872-7557. ; 161, s. 259-267 Tidskriftsartikel (refereegranskat)abstract Having lower quantization resolution, has been introduced in the literature, to reduce the power consumption of massive MIMO and millimeter wave MIMO systems. Here, we analyze the bit error rate (BER) performance of quantized uplink massive MIMO employing few-bit resolution ADCs. Considering ZF detection, we derive a signal-to-interference, quantization and noise ratio (SIQNR) to achieve an analytical BER approximation for coarsely quantized M-QAM massive MIMO systems, by using a linear quantization model. The proposed expression is a function of the quantization resolution in bits. We further numerically investigate the effects of different quantization levels, from 1-bit to 4-bits, on the BER of three modulation types QPSK, 16-QAM, and 64-QAM. The uniform and non-uniform quantizers are employed in our simulation. Monte Carlo simulation results reveal that our approximate formula gives a tight upper bound on the BER performance of b-bit resolution quantized systems using non-uniform quantizers, whereas the use of uniform quantizers cause a lower performance. We also found a small BER performance degradation in coarsely quantized systems, for example 2-3 bits QPSK and 3-4 bits 16-QAM, compared to the full-precision (unquantized) case. However, this performance degradation can be compensated by increasing the number of antennas at the BS. (C) 2019 Published by Elsevier B.V.
29.	Babu, Prabhu, et al. (författare) Connection between SPICE and Square-Root LASSO for sparse parameter estimation 2014 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 95, s. 10-14 Tidskriftsartikel (refereegranskat)abstract In this note we show that the sparse estimation technique named Square-Root LASSO (SR-LASSO) is connected to a previously introduced method named SPICE. More concretely we prove that the SR-LASSO with a unit weighting factor is identical to SPICE. Furthermore we show via numerical simulations that the performance of the SR-LASSO changes insignificantly when the weighting factor is varied. SPICE stands for sparse iterative covariance-based estimation and LASSO for least absolute shrinkage and selection operator.
30.	Babu, Prabhu, et al. (författare) Multiple-hypothesis testing rules for high-dimensional model selection and sparse-parameter estimation 2023 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 213 Tidskriftsartikel (refereegranskat)abstract We consider the problem of model selection for high-dimensional sparse linear regression models. We pose the model selection problem as a multiple-hypothesis testing problem and employ the methods of false discovery rate (FDR) and familywise error rate (FER) to solve it. We also present the reformulation of the FDR/FER-based approaches as criterion-based model selection rules and establish their relation to the extended Bayesian Information Criterion (EBIC), which is a state-of-the-art high-dimensional model selection rule. We use numerical simulations to show that the proposed FDR/FER method is well suited for high-dimensional model selection and performs better than EBIC.
31.	Bastianello, Nicola, et al. (författare) Extrapolation-Based Prediction-Correction Methods for Time-varying Convex Optimization 2023 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 210 Tidskriftsartikel (refereegranskat)abstract In this paper, we focus on the solution of online optimization problems that arise often in signal processing and machine learning, in which we have access to streaming sources of data. We discuss algorithms for online optimization based on the prediction-correction paradigm, both in the primal and dual space. In particular, we leverage the typical regularized least-squares structure appearing in many signal processing problems to propose a novel and tailored prediction strategy, which we call extrapolation-based. By using tools from operator theory, we then analyze the convergence of the proposed methods as applied both to primal and dual problems, deriving an explicit bound for the tracking error, that is, the distance from the time-varying optimal solution. We further discuss the empirical performance of the algorithm when applied to signal processing, machine learning, and robotics problems.
32.	Bian, Xiao, et al. (författare) Bi-sparsity pursuit: A paradigm for robust subspace recovery 2018 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 152, s. 148-152 Tidskriftsartikel (refereegranskat)
33.	Bokaei, Mohammad, et al. (författare) Harmonic retrieval using weighted lifted-structure low-rank matrix completion 2024 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 216 Tidskriftsartikel (refereegranskat)abstract In this paper, we investigate the problem of recovering the frequency components of a mixture of K complex sinusoids from a random subset of N equally-spaced time-domain samples. Because of the random subset, the samples are effectively non-uniform. Besides, the frequency values of each of the K complex sinusoids are assumed to vary continuously within a given range. For this problem, we propose a two-step strategy: (i) we first lift the incomplete set of uniform samples (unavailable samples are treated as missing data) into a structured matrix with missing entries, which is potentially low-rank; then (ii) we complete the matrix using a weighted nuclear minimization problem. We call the method a weighted lifted-structured (WLi) low-rank matrix recovery. Our approach can be applied to a range of matrix structures such as Hankel and double-Hankel, among others, and provides improvement over the unweighted existing schemes such as EMaC and DEMaC. We provide theoretical guarantees for the proposed method, as well as numerical simulations in both noiseless and noisy settings. Both the theoretical and the numerical results confirm the superiority of the proposed approach.
34.	Borpatra Gohain, Prakash, et al. (författare) Scale-Invariant and consistent Bayesian information criterion for order selection in linear regression models 2022 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 196 Tidskriftsartikel (refereegranskat)abstract The Bayesian information criterion (BIC) is one of the most well-known criterion used for model order estimation in linear regression models. However, in its popular form, BIC is inconsistent as the noise variance tends to zero given that the sample size is small and fixed. Several modifications of the original BIC have been proposed that takes into account the high-SNR consistency, but it has been recently observed that the performance of the high-SNR forms of BIC highly depends on the scaling of the data. This scaling problem is a byproduct of the data dependent penalty design, which generates irregular penalties when the data is scaled and often leads to greater underfitting or overfitting losses in some scenarios when the noise variance is too small or large. In this paper, we present a new form of the BIC for order selection in linear regression models where the parameter vector dimension is small compared to the sample size. The proposed criterion eliminates the scaling problem and at the same time is consistent for both large sample sizes and high-SNR scenarios.
35.	Brynolfsson, Johan, et al. (författare) A time-frequency-shift invariant parameter estimator for oscillating transient functions using the matched window reassignment 2021 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 183 Tidskriftsartikel (refereegranskat)abstract In this paper we present the matched window reassignment method, generalizing the results to complex valued signals in multiple dimensions. For an oscillating transient signal with an envelope shape described by an arbitrary twice differentiable function, the reassigned spectrogram, with a matched window, concentrates all energy into one single time-frequency point. An estimator for the parameters of the envelope, in multiple dimensions, is constructed using the above property where the concentration is measured using the Rényi entropy. Furthermore, we present a classification scheme, where an observation is classified based on the concentration when reassigning with a set of model functions. Finally, two examples of parameter estimation from real-world measurements are shown, a one-dimensional time series of a single dolphin click and a two-dimensional time-series of seismic data.
36.	Brynolfsson, Johan, et al. (författare) Parameter estimation of Oscillating Gaussian functions using the scaled reassigned spectrogram 2018 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 150, s. 20-32 Tidskriftsartikel (refereegranskat)abstract In this paper we suggest an algorithm for estimation of the parameters detailing Oscillating Gaussian functions. The different components of the signal are first detected in the spectrogram. After this we exploit the fact that a Gaussian function may be perfectly reassigned into one single point given a correct scaling factor, where this scaling factor is a function of the unknown shape parameter of the Gaussian function. The scaled reassignment of the spectrogram is performed using a set of candidate scaling factors and the local Renyi entropy is used to measure the concentration of each component using every candidate scaling factor. The estimates are refined by using non-linear least squares. The algorithm is evaluated on both simulated and real data.
37.	Burak Guldogan, Mehmet, et al. (författare) Multipath channel identification by using global optimization in ambiguity function domain 2011 Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 91:11, s. 2647-2660 Tidskriftsartikel (refereegranskat)abstract A new transform domain array signal processing technique is proposed for identification of multipath communication channels. The received array element outputs are transformed to delay-Doppler domain by using the cross-ambiguity function (CAF) for efficient exploitation of the delay-Doppler diversity of the multipath components. Clusters of multipath components can be identified by using a simple amplitude thresholding in the delay-Doppler domain. Particle swarm optimization (PSO) can be used to identify parameters of the multipath components in each cluster. The performance of the proposed PSO-CAF technique is compared with the space alternating generalized expectation maximization (SAGE) technique and with a recently proposed PSO based technique at various SNR levels. Simulation results clearly quantify the superior performance of the PSO-CAF technique over the alternative techniques at all practically significant SNR levels.
38.	Burgess, Simon, et al. (författare) TOA sensor network self-calibration for receiver and transmitter spaces with difference in dimension 2015 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 107:Online 11 June 2014, s. 33-42 Tidskriftsartikel (refereegranskat)abstract We study and solve the previously unstudied problem of finding both transmitter and receiver positions using only time of arrival (TOA) measurements when there is a difference in dimensionality between the affine subspaces spanned by receivers and transmitters. Anchor-free TOA network calibration has uses both in radio, radio strength and sound applications, such as calibrating ad hoc microphone arrays. Using linear techniques and requiring only minimal number of receivers and transmitters, an algorithm is constructed for general dimension p for the lower dimensional subspace. Degenerate cases are determined and partially characterized as when receivers or transmitters inhabit a lower dimensional affine subspace than was given as input. The algorithm is further extended to overdetermined cases in a straightforward manner. Utilizing the minimal solver, an algorithm using the Random Sample Consensus (RANSAC) paradigm has been constructed to simultaneously solve the calibration problem and remove severe outliers, a common problem in TOA applications. Simulated experiments show good performance for the minimal solver and the RANSAC-like algorithm under noisy measurements. Two indoor environment experiments using microphones and speakers give a RMSE of 2.35 cm and 3.95 cm on receiver and transmitter positions compared to computer vision reconstructions.
39.	Cang, Siyuan, et al. (författare) Toeplitz-based blind deconvolution of underwater acoustic channels using wideband integrated dictionaries 2021 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 179 Tidskriftsartikel (refereegranskat)abstract In this paper, we propose a blind channel deconvolution method based on a sparse reconstruction framework exploiting a wideband dictionary under the (relatively weak) assumption that the transmitted signal may be assumed to be well modelled as a sum of sinusoids. Using a Toeplitz structured formulation of the received signal, we form an iterative blind deconvolution scheme, alternatively estimating the underwater impulse response and the transmitted waveform. The resulting optimization problems are convex, and we formulate a computationally efficient solver using the Alternating Direction Method of Multipliers (ADMM). We illustrate the performance of the resulting estimator using both simulated and measured underwater signals.
40.	Chatterjee, Saikat, et al. (författare) Optimum switched split vector quantization of LSF parameters 2008 Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 88:6, s. 1528-1538 Tidskriftsartikel (refereegranskat)
41.	Christensen, M, et al. (författare) Multi-pitch estimation 2008 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 88:4, s. 972-983 Tidskriftsartikel (refereegranskat)abstract In this paper, we formulate the multi-pitch estimation problem and propose a number of methods to estimate the set of fundamental frequencies. The proposed methods, based on the nonlinear least-squares (NLS), Multiple Signal Classification (MUSIC) and the Capon principles, estimate the multiple fundamental frequencies via a number of one-dimensional searches. We also propose an iterative method based on the Expectation Maximization (EM) algorithm. The statistical properties of the methods are evaluated via Monte Carlo simulations for both the single- and multi-pitch cases.
42.	Chung, P. J., et al. (författare) Broadband ML estimation under model order uncertainty 2010 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 90:5, s. 1350-1356 Tidskriftsartikel (refereegranskat)abstract The number of signals hidden in data plays a crucial role in array processing. When this information is not available, conventional approaches apply information theoretic criteria or multiple hypothesis tests to simultaneously estimate model order and parameter. These methods are usually computationally intensive, since ML estimates are required for a hierarchy of nested models. In this contribution, we propose a computationally efficient solution to avoid this full search procedure and address issues unique to the broadband case. Our max-search approach computes ML estimates only for the maximally hypothesized number of signals, and selects relevant components through hypothesis testing. Furthermore, we introduce a criterion based on the rank of the steering matrix to reduce indistinguishable components caused by overparameterization. Numerical experiments show that despite model order uncertainty, the proposed method achieves comparable estimation and detection accuracy as standard methods, but at much lower computational expense. (C) 2009 Elsevier B.V. All rights reserved.
43.	Ding, Xinghao, et al. (författare) High-resolution source localization exploiting the sparsity of the beamforming map 2022 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 192 Tidskriftsartikel (refereegranskat)abstract Beamforming technology plays a significant role in source localization and quantification. As traditional delay-and-sum beamformers generally yield low spatial resolution, as well as suffer from the occurrence of spurious sources, different forms of deconvolution methods have been proposed in the literature. In this work, we propose two approaches based on a sparse reconstruction framework combined with the use of the Fourier-based efficient implementation techniques. Numerical simulations and experimental data analysis show the effectiveness and advantages of the proposed methods.
44.	Eghbali, Amir, et al. (författare) A class of reconfigurable and low-complexity two-stage Nyquist filters 2014 Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 96, s. 164-172 Tidskriftsartikel (refereegranskat)abstract This paper introduces a class of reconfigurable two-stage Nyquist filters where the Farrow structure realizes the polyphase components of linear-phase finite-length impulse response (FIR) filters. By adjusting the variable predetermined multipliers of the Farrow structure, various linear-phase FIR Nyquist filters and integer interpolation/decimation structures are obtained, online. However, the filter design problem is solved only once, offline. Design examples, based on the reweighted l(1)-norm minimization, illustrate the proposed method. Savings in the arithmetic complexity are obtained when compared to the reconfigurable single-stage structures.
45.	Eghbali, Amir, et al. (författare) A method for the design of Farrow-structure based variable fractional-delay FIR filters 2013 Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 93:5, s. 1341-1348 Tidskriftsartikel (refereegranskat)abstract This paper proposes a method to design variable fractional-delay (FD) filters using the Farrow structure. In the transfer function of the Farrow structure, different subfilters are weighted by different powers of the FD value. As both the FD value and its powers are smaller than 0.5, our proposed method uses them as diminishing weighting functions. The approximation error, for each subfilter, is then increased in proportion to the power of the FD value. This gives a new distribution for the orders of the Farrow subfilters which has not been utilized before. This paper also includes these diminishing weighting functions in the filter design so as to obtain their optimal values, iteratively. We consider subfilters of both even and odd orders. Examples illustrate our proposed method and comparisons, to various earlier designs, show a reduction of the arithmetic complexity.
46.	Eghbali, Amir, et al. (författare) Conditions for Lth-band filters of order 2N as cascades of identical linear-phase FIR spectral factors of order N 2014 Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 97:April Tidskriftsartikel (refereegranskat)abstract This paper presents formulas for the number of optimization parameters (degrees of freedom) when designing Type I linear-phase finite-length impulse response (FIR) Lth-band filters of order 2N as cascades of identical linear-phase FIR spectral factors of order N. We deal with two types of degrees of freedom referred to as (i) the total degrees of freedom D-T, and (ii) the remaining degrees of freedom D-R. Due to the symmetries or antisymmetries in the impulse responses of the spectral factors, D-T roughly equals N/2. Some of these parameters are specifically needed to meet the Lth-band conditions because, in an Lth-band filter, every Lth coefficient is zero and the center tap equals 1/L. The remaining D-R parameters can then be used to improve the stopband characteristics of the overall Lth-band filter. We derive general formulas for D-R with given pairs of L and N. It is shown that for a fixed L, the choices of N, in a close neighborhood, may even decrease D-R despite increasing the arithmetic complexity, order, and the delay.
47.	Einemo, Martin, et al. (författare) Weighted least squares algorithm for target localization in distributed MIMO radar 2015 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 115, s. 144-150 Tidskriftsartikel (refereegranskat)abstract In this paper, we address the problem of locating a target using multiple-input multiple-output (MIMO) radar with widely separated antennas. Through linearizing the bistatic range measurements, which correspond to the sum of transmitter-to-target and target-to-receiver distances, a quadratically constrained quadratic program (QCQP) for target localization is formulated. The solution of the QCQP is proved to be an unbiased position estimate whose variance equals the Cramer-Rao lower bound. A weighted least squares algorithm is developed to realize the QCQP. Simulation results are included to demonstrate the high accuracy of the proposed MIMO radar positioning approach.
48.	Ekblad, Ulf, et al. (författare) Theoretical foundation of the intersecting cortical model and its use for change detection of aircraft, cars, and nuclear explosion tests 2004 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 84:7, s. 1131-1146 Tidskriftsartikel (refereegranskat)abstract The intersecting cortical model (ICM) is a model based on neural network techniques especially designed for image processing. It was derived from several visual cortex models and is basically the intersection of these models, i.e. the common elements amongst these models. The theoretical foundation of the ICM is given and it is shown how the ICM can be derived as a reduced set of equations of the pulse-coupled neural network based upon models proposed by Eckhorn and Reitboeck. Tests of the ICM are presented: one on a series of images of an aircraft moving in the sky; two on car detection; and one on preparations of underground nuclear explosions. The ICM is shown here, in a few examples, to be useful in imagery change detection: aircraft moving against a homogeneous background without precise geometric matching; car on a road; two cars moving in an urban setting without precise geometric matching; and for a linear structure in a complex background. The ICM can be used when the moving objects are not too small and the background is not too difficult. Changes involving larger linear structures can be detected even if the background is not homogeneous.
49.	Elvander, Filip, et al. (författare) An Adaptive Penalty Multi-Pitch Estimator with Self-Regularization 2016 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 127, s. 56-70 Tidskriftsartikel (refereegranskat)abstract This work treats multi-pitch estimation, and in particular the common misclassification issue wherein the pitch at half the true fundamental frequency, the sub-octave, is chosen instead of the true pitch. Extending on current group LASSO-based methods for pitch estimation, this work introduces an adaptive total variation penalty, which enforces both group- and block sparsity, as well as deals with errors due to sub-octaves. Also presented is a scheme for signal adaptive dictionary construction and automatic selection of the regularization parameters. Used together with this scheme, the proposed method is shown to yield accurate pitch estimates when evaluated on synthetic speech data. The method is shown to perform as good as, or better than, current state-of-the-art sparse methods while requiring fewer tuning parameters than these, as well as several con- ventional pitch estimation methods, even when these are given oracle model orders. When evaluated on a set of ten musical pieces, the method shows promising results for separating multi-pitch signals.
50.	Elvander, Filip, et al. (författare) Multi-dimensional grid-less estimation of saturated signals 2018 Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 145, s. 37-47 Tidskriftsartikel (refereegranskat)abstract This work proposes a multi-dimensional frequency and amplitude estimator tailored for noise corrupted signals that have been clipped. Formulated as a sparse reconstruction problem, the proposed algorithm estimates the signal parameters by solving an atomic norm minimization problem. The estimator also exploits the waveform information provided by the clipped samples, incorporated in the form of linear constraints that have been augmented by slack variables as to provide robustness to noise. Numerical examples indicate that the algorithm offers preferable performance as compared to methods not exploiting the saturated samples.

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