Pub Date : 1997-07-21DOI: 10.1109/HOST.1997.613501
J.Y. Kim, K. Cho, Y. Kim, J.H. Chung, S. Nam
In this paper, a new Volterra series-based adaptive preprocessing technique is presented to linearize weakly nonlinear systems with their linear parts being invertible. In particular, a systematic but simple design procedure is proposed for the compensation of system nonlinearities up to a required order, yielding a substantial reduction of computation burden. For the performance test of the proposed approach, some simulation results are also provided.
{"title":"Design of a Volterra series-based nonlinear compensator","authors":"J.Y. Kim, K. Cho, Y. Kim, J.H. Chung, S. Nam","doi":"10.1109/HOST.1997.613501","DOIUrl":"https://doi.org/10.1109/HOST.1997.613501","url":null,"abstract":"In this paper, a new Volterra series-based adaptive preprocessing technique is presented to linearize weakly nonlinear systems with their linear parts being invertible. In particular, a systematic but simple design procedure is proposed for the compensation of system nonlinearities up to a required order, yielding a substantial reduction of computation burden. For the performance test of the proposed approach, some simulation results are also provided.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131409828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-07-21DOI: 10.1109/HOST.1997.613547
P. Campisi, G. Scarano
The computational aspects related to sample estimation of moments involving certain "piecewise" nonlinearities are addressed with application to DOA estimation. In particular, the accuracy vs. computational saving tradeoff associated to "soft-limiting" nonlinearities can be exploited to simplify the computation of sample covariances without resulting in significative accuracy loss. It is also shown how, in sample cumulants evaluation, this approach can be employed to reduce the overall number of arithmetic operations using nonlinearities which act separately on the real and the imaginary parts of complex numbers.
{"title":"Computational savings using nonlinear statistics in DOA estimation","authors":"P. Campisi, G. Scarano","doi":"10.1109/HOST.1997.613547","DOIUrl":"https://doi.org/10.1109/HOST.1997.613547","url":null,"abstract":"The computational aspects related to sample estimation of moments involving certain \"piecewise\" nonlinearities are addressed with application to DOA estimation. In particular, the accuracy vs. computational saving tradeoff associated to \"soft-limiting\" nonlinearities can be exploited to simplify the computation of sample covariances without resulting in significative accuracy loss. It is also shown how, in sample cumulants evaluation, this approach can be employed to reduce the overall number of arithmetic operations using nonlinearities which act separately on the real and the imaginary parts of complex numbers.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129227717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-07-21DOI: 10.1109/HOST.1997.613530
A. Swami, Brian M. Sadler
We address the problem of time-delay estimation (TDE) and direction-of-arrival (DOA) estimation in the presence of symmetric alpha-stable noise. We show that these problems can be handled by conventional correlation or cumulant based techniques, provided that the noisy signals are first passed through a generic zero-memory non-linearity. This pre-processing is also useful in the detection context. We also address the problem of blind linear system identification, where the input is an iid alpha-stable process; we show that consistent estimates of the possibly non-minimum phase ARMA parameters can be obtained by using self-normalized correlations and cumulants. Theoretical arguments are supported by simulations.
{"title":"TDE, DOA and related parameter estimation problems in impulsive noise","authors":"A. Swami, Brian M. Sadler","doi":"10.1109/HOST.1997.613530","DOIUrl":"https://doi.org/10.1109/HOST.1997.613530","url":null,"abstract":"We address the problem of time-delay estimation (TDE) and direction-of-arrival (DOA) estimation in the presence of symmetric alpha-stable noise. We show that these problems can be handled by conventional correlation or cumulant based techniques, provided that the noisy signals are first passed through a generic zero-memory non-linearity. This pre-processing is also useful in the detection context. We also address the problem of blind linear system identification, where the input is an iid alpha-stable process; we show that consistent estimates of the possibly non-minimum phase ARMA parameters can be obtained by using self-normalized correlations and cumulants. Theoretical arguments are supported by simulations.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131053455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-07-21DOI: 10.1109/HOST.1997.613520
Haralambos Pozidis, A. P. Petroupulu
System reconstruction from arbitrarily selected slices of the n-th order output spectrum is considered. We establish that unique identification of the impulse response of a system can be performed, up to a scalar and a circular shift, based on any two horizontal slices of the discretized n-th order output spectrum, (n/spl ges/3), as long as the distance between the slices and the grid size satisfy a simple condition. For the special case of real systems, one slice suffices for reconstruction. The ability to select the slices to be used for reconstruction enables one to avoid regions of the n-th order spectrum where the estimation variance is high, or where the ideal bispectrum is expected to be zero, as in the case of bandlimited systems. We propose a mechanism for selecting slices that result in improved system estimates. We also demonstrate via simulations the superiority, in terms of estimation bias and variance, of the proposed method over existing approaches in the case of bandlimited systems.
{"title":"System reconstruction from selected HOS regions","authors":"Haralambos Pozidis, A. P. Petroupulu","doi":"10.1109/HOST.1997.613520","DOIUrl":"https://doi.org/10.1109/HOST.1997.613520","url":null,"abstract":"System reconstruction from arbitrarily selected slices of the n-th order output spectrum is considered. We establish that unique identification of the impulse response of a system can be performed, up to a scalar and a circular shift, based on any two horizontal slices of the discretized n-th order output spectrum, (n/spl ges/3), as long as the distance between the slices and the grid size satisfy a simple condition. For the special case of real systems, one slice suffices for reconstruction. The ability to select the slices to be used for reconstruction enables one to avoid regions of the n-th order spectrum where the estimation variance is high, or where the ideal bispectrum is expected to be zero, as in the case of bandlimited systems. We propose a mechanism for selecting slices that result in improved system estimates. We also demonstrate via simulations the superiority, in terms of estimation bias and variance, of the proposed method over existing approaches in the case of bandlimited systems.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"383 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116327817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-07-21DOI: 10.1109/HOST.1997.613543
M. Gaeta, F. Briolle, P. Esparcieux
In underwater acoustics, the signal received by sensors is a mixture of different elementary sources, filtered by the environment. In blind separation of sources, we can isolate each source from different mixtures of sources without any a priori information, except for assuming statistical independence of the different sources. Jutten and Herault (1991) proposed a neuromimetic solution to the problem. In our work, we use this solution to separate convolutive mixtures of simulated complex underwater signals in a shallow water environment. To allow multipath identification a whitening step has to be introduced. We propose a local whitening procedure that does not impact the separated signal output and preserves the signal characteristics. This promising technique can be improved using non causal whitening filters more adapted to the target environment.
{"title":"Blind separation of sources applied to convolutive mixtures in shallow water","authors":"M. Gaeta, F. Briolle, P. Esparcieux","doi":"10.1109/HOST.1997.613543","DOIUrl":"https://doi.org/10.1109/HOST.1997.613543","url":null,"abstract":"In underwater acoustics, the signal received by sensors is a mixture of different elementary sources, filtered by the environment. In blind separation of sources, we can isolate each source from different mixtures of sources without any a priori information, except for assuming statistical independence of the different sources. Jutten and Herault (1991) proposed a neuromimetic solution to the problem. In our work, we use this solution to separate convolutive mixtures of simulated complex underwater signals in a shallow water environment. To allow multipath identification a whitening step has to be introduced. We propose a local whitening procedure that does not impact the separated signal output and preserves the signal characteristics. This promising technique can be improved using non causal whitening filters more adapted to the target environment.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121705721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-07-21DOI: 10.1109/HOST.1997.613477
Ying-Chang Liang, A. R. Leyman, B. Soong
This paper addresses the problem of time delay estimation (TDE) in spatially correlated noises. Two cases are considered: (i) TDE of non-Gaussian signal in spatially correlated Gaussian noises; and (ii) TDE of Gaussian signal in spatially correlated non-Gaussian noises. For the first case, a new approach based upon the use of higher order statistics of the measurements is proposed; for the second case, a hybrid approach by using higher and second order statistics of the measurements is suggested. Simulation examples are presented to illustrate the effectiveness of these approaches.
{"title":"Multipath time delay estimation using higher order statistics","authors":"Ying-Chang Liang, A. R. Leyman, B. Soong","doi":"10.1109/HOST.1997.613477","DOIUrl":"https://doi.org/10.1109/HOST.1997.613477","url":null,"abstract":"This paper addresses the problem of time delay estimation (TDE) in spatially correlated noises. Two cases are considered: (i) TDE of non-Gaussian signal in spatially correlated Gaussian noises; and (ii) TDE of Gaussian signal in spatially correlated non-Gaussian noises. For the first case, a new approach based upon the use of higher order statistics of the measurements is proposed; for the second case, a hybrid approach by using higher and second order statistics of the measurements is suggested. Simulation examples are presented to illustrate the effectiveness of these approaches.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131802937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-07-21DOI: 10.1109/HOST.1997.613566
P. Amblard, J. Brossier, J. Lacoume
In this paper, we consider some independent problems concerning HOS and nonGaussian long range dependent processes. We exhibit HOS for non integer FARIMA processes, showing that singularities may occur in multispectrum. A class of nonGaussian processes constructed by a multiplicative process on the dyadic tree is then considered. Finally, long range dependence problems in the Fourier transform are examined.
{"title":"Playing with long range dependence and HOS","authors":"P. Amblard, J. Brossier, J. Lacoume","doi":"10.1109/HOST.1997.613566","DOIUrl":"https://doi.org/10.1109/HOST.1997.613566","url":null,"abstract":"In this paper, we consider some independent problems concerning HOS and nonGaussian long range dependent processes. We exhibit HOS for non integer FARIMA processes, showing that singularities may occur in multispectrum. A class of nonGaussian processes constructed by a multiplicative process on the dyadic tree is then considered. Finally, long range dependence problems in the Fourier transform are examined.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130756677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-07-21DOI: 10.1109/HOST.1997.613559
Robert D. Pierce
Many physical phenomena are non-Gaussian and if the observed data have frequently occurring extreme values, then the phenomena may be modeled as a random process with an alpha-stable distribution. When positive and negative outcomes are equally likely, then the process would be symmetric alpha-stable (S/spl alpha/S); however when only positive outcomes are possible, then the process would be positive alpha-stable (P/spl alpha/S). Phenomena related to energy or power are examples. This paper presents the characteristics and potential applications for the P/spl alpha/S distribution. For this distribution all negative-order moments exist, and ratios of these moments are used to estimate alpha. Application areas that are examined include: seismic activity, ocean wave variability, and radar sea clutter modulation. The correlation properties of these data are examined.
{"title":"Application of the positive alpha-stable distribution","authors":"Robert D. Pierce","doi":"10.1109/HOST.1997.613559","DOIUrl":"https://doi.org/10.1109/HOST.1997.613559","url":null,"abstract":"Many physical phenomena are non-Gaussian and if the observed data have frequently occurring extreme values, then the phenomena may be modeled as a random process with an alpha-stable distribution. When positive and negative outcomes are equally likely, then the process would be symmetric alpha-stable (S/spl alpha/S); however when only positive outcomes are possible, then the process would be positive alpha-stable (P/spl alpha/S). Phenomena related to energy or power are examples. This paper presents the characteristics and potential applications for the P/spl alpha/S distribution. For this distribution all negative-order moments exist, and ratios of these moments are used to estimate alpha. Application areas that are examined include: seismic activity, ocean wave variability, and radar sea clutter modulation. The correlation properties of these data are examined.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129086852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-07-21DOI: 10.1109/HOST.1997.613482
I. Jouny, A. Low
The bispectrum of a direct sequence spread spectrum communication signal contaminated with coupled multitone jamming provides significant information about the jammer frequencies and thus permits its excision using a bank of notch filters. Jammers that can be modeled as an autoregressive process can also be examined in the bispectral domain and mitigated using a linear FIR filter with temporally changing coefficients. The results indicate that utilizing bispectral analysis in DS spread spectrum communications is an attractive alternative to conventional excision techniques and in some scenarios the only excision option available.
{"title":"Coherent interference excision using higher order spectra","authors":"I. Jouny, A. Low","doi":"10.1109/HOST.1997.613482","DOIUrl":"https://doi.org/10.1109/HOST.1997.613482","url":null,"abstract":"The bispectrum of a direct sequence spread spectrum communication signal contaminated with coupled multitone jamming provides significant information about the jammer frequencies and thus permits its excision using a bank of notch filters. Jammers that can be modeled as an autoregressive process can also be examined in the bispectral domain and mitigated using a linear FIR filter with temporally changing coefficients. The results indicate that utilizing bispectral analysis in DS spread spectrum communications is an attractive alternative to conventional excision techniques and in some scenarios the only excision option available.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115405343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-07-21DOI: 10.1109/HOST.1997.613557
M. Coulon, J. Tourneret, M. Ghogho
The detection of two spectrally equivalent (SE) processes is addressed. The two SE processes are modeled using two SE parametric models: the noisy AR model and the ARMA model. Higher-order statistics are shown to be an efficient tool for the SE process detection problem. A new detector based on the higher-order Yule-Walker matrix singularity is studied. The detector performance is compared in supervised and unsupervised learning. The model order mismatch is then studied.
{"title":"Detection and classification of spectrally equivalent processes: a parametric approach","authors":"M. Coulon, J. Tourneret, M. Ghogho","doi":"10.1109/HOST.1997.613557","DOIUrl":"https://doi.org/10.1109/HOST.1997.613557","url":null,"abstract":"The detection of two spectrally equivalent (SE) processes is addressed. The two SE processes are modeled using two SE parametric models: the noisy AR model and the ARMA model. Higher-order statistics are shown to be an efficient tool for the SE process detection problem. A new detector based on the higher-order Yule-Walker matrix singularity is studied. The detector performance is compared in supervised and unsupervised learning. The model order mismatch is then studied.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116903204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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