| 1. |
- van de Beek, Jan-Jaap, et al.
(författare)
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Three non-pilot based time- and frequency estimators for OFDM
- 2000
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Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 80:7, s. 1321-1334
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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.
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| 2. |
- Wahlberg, Patrik, et al.
(författare)
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Methods for alignment of multi-class signal sets
- 2003
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Ingår i: Signal Processing. - 0165-1684. ; 83:5, s. 983-1000
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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.
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| 3. |
- Anderson, Sören
(författare)
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On Optimal Dimension Reduction for Sensor Array Signal Processing
- 1993
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 30:2, s. 245-256
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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.
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| 4. |
- Carlsson, B, et al.
(författare)
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A NOTCH FILTER BASED ON RECURSIVE LEAST-SQUARES MODELING
- 1994
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 35:3, s. 231-239
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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.
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| 5. |
- Elias, Elizabeth, et al.
(författare)
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Tree-structured IIR/FIR uniform-band and octave-band filter banks with very low-complexity analysis or synthesis filters
- 2003
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Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 83:9, s. 1997-2009
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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.
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| 6. |
- Granlund, Gösta
(författare)
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The Complexity of Vision
- 1999
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Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 74:1, s. 101-126
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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.
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| 7. |
- Händel, Peter, 1962-, et al.
(författare)
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Asymptotic noise gain of polynomial predictors
- 1997
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Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 62:2, s. 247-250
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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.
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| 8. |
- Händel, Peter, 1962-, et al.
(författare)
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Asymptotic variance of the AR spectral estimator for noisy sinusoidal data
- 1994
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 35:2, s. 131-139
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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.
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| 9. |
- Händel, Peter, 1962-
(författare)
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High-order Yule-Walker estimation of the parameters of exponentially damped cisoids in noise
- 1993
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Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 32:3, s. 315-328
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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.
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| 10. |
- Händel, Peter, 1962-, et al.
(författare)
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Performance analysis of a correlation based single tone frequency estimator
- 1995
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Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 44:2, s. 223-231
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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.
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