| 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. |
- 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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| 4. |
- Koeck, Philip J B
(författare)
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Quantization errors in averaged digitized data
- 2001
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Ingår i: Signal Processing. - 0165-1684 .- 1872-7557. ; 81:2, s. 345-356
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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.
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| 5. |
- Larsson, Erik G., et al.
(författare)
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Spectral estimation via adaptive filterbank methods : a unified analysis and a new algorithm
- 2002
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Ingår i: Signal Processing. - Amsterdam, The Netherlands : Elsevier. - 0165-1684 .- 1872-7557. ; 82:12, s. 1991-2001
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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.
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| 6. |
- Ekblad, Ulf, et al.
(författare)
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Theoretical foundation of the intersecting cortical model and its use for change detection of aircraft, cars, and nuclear explosion tests
- 2004
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 84:7, s. 1131-1146
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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.
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| 7. |
- Erdogmus, Deniz, et al.
(författare)
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Asymptotic SNR-performance of some image combination techniques for phased-array MRI
- 2004
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Ingår i: Signal Processing. - Amsterdam, The Netherlands : Elsevier. - 0165-1684 .- 1872-7557. ; 84:6, s. 997-1003
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Tidskriftsartikel (refereegranskat)abstract
- Phased-array magnetic resonance imaging technology is currently flourishing with the promise of obtaining a profitable trade-off between image quality and image acquisition speed. The image quality is generally measured in terms of the signal-to-noise ratio (SNR), which is often calculated using samples taken from the reconstructed image. In this paper, we derive analytical expressions for the asymptotic SNR in the final image for three different phased-array image combination methods, namely: (1) sum-of-squares, (2) singular value decomposition, and (3) normalized coil averaging. The SNR expressions are expressed in terms of the statistics of the noise in the measurements, as well as the coil sensitivity coefficients. Our results can facilitate a better understanding for the phased-array image combination problem, as well as provide a tool for the optimal design of coils.
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| 8. |
- Erdogmus, Deniz, et al.
(författare)
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Measuring the signal-to-noise ratio in magnetic resonance imaging: a caveat
- 2004
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Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 84:6, s. 1035-1040
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Tidskriftsartikel (refereegranskat)abstract
- The validity of the signal-to-noise ratio (SNR) as an objective quality measure for biomedical images has been the subject of a long-standing debate. Nevertheless, the SNR is the most popularly used measure both for assessing the quality of images and for evaluating the effectiveness of image enhancement and signal processing techniques. In this correspondence, we illustrate that under certain conditions the SNR can be changed by a nonlinear transformation, and also that it is often hard to measure objectively. Therefore, the issue is not only how well the SNR correlates with image quality as perceived by a human observer (which has been the primary subject of earlier debate), but also that SNR is questionable from a quantitative measurement point of view.
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| 9. |
- Ganesan, G, et al.
(författare)
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HOS-based orthogonal subspace algorithm for causal ARMA system identification
- 2000
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Ingår i: SIGNAL PROCESSING. - : ELSEVIER SCIENCE BV. - 0165-1684. ; 80:3, s. 535-542
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Tidskriftsartikel (refereegranskat)abstract
- In this paper a new method, based on subspaces of a cumulant matrix, is proposed for the blind identification of an ARMA system which is driven by white non-Gaussian noise. The relationship between the cumulants and the impulse response is exploited to ar
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| 10. |
- Johansson, Rolf, et al.
(författare)
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On Behavioral Model Identification
- 2004
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 84:7, s. 1089-1100
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents theory andalgorithms for system identification suitable for the framework of behavioral system theory. An algorithm basedon algebraic system theory and realization theory (Ho-Kalman realization) in a subspace model identification framework is presented. The novel approach taken consists of the formulation of input-output data as an impulse response model and the subsequent application of state-space realization. The method provides an approximation framework for simultaneous model identification and signal reconstruction.
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