Pub Date : 1992-10-07DOI: 10.1109/SSAP.1992.246898
D. Sherman, M. Zoltowski
The alpha wave is often harmonically related or coupled to frequencies in other EEG bands. Several autoregressive and eigenstructure-based bispectral algorithms have proven to be effective in the detection and estimation of alpha coupling. The authors extend the triple Kronecker product method of Swindlehurst and Kailath (1989) to estimation of biphases through a generalized eigenvalue approach. As a major concentration of significant bispectral peaks lie in the alpha-alpha coupling region, low model order can be used for accurate results with these methods.<>
{"title":"Decomposing the alpha rhythms: comparative performance evaluation of parametric bispectral algorithms for EEG","authors":"D. Sherman, M. Zoltowski","doi":"10.1109/SSAP.1992.246898","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246898","url":null,"abstract":"The alpha wave is often harmonically related or coupled to frequencies in other EEG bands. Several autoregressive and eigenstructure-based bispectral algorithms have proven to be effective in the detection and estimation of alpha coupling. The authors extend the triple Kronecker product method of Swindlehurst and Kailath (1989) to estimation of biphases through a generalized eigenvalue approach. As a major concentration of significant bispectral peaks lie in the alpha-alpha coupling region, low model order can be used for accurate results with these methods.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122364167","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246792
G. Jacovitti, A. Laurenti, A. Neri
In some DOA applications, the M sensors of the array can be affected by spatially uncorrelated white noise having power levels different from sensor to sensor. Such a noise power unbalance induces severe bias errors of DOA estimates performed by eigenspace based methods. In some instances, an estimate of the ratio between the noise variances of the sensors is available, so that a noise pre-compensation procedure can be conceived. For this purpose, a generalized AR estimator is considered in connection with the signal enhancement approach. Simulation examples illustrate the method.<>
{"title":"A generalized AR operator for non-uniform noise compensation in DOA signal enhancement","authors":"G. Jacovitti, A. Laurenti, A. Neri","doi":"10.1109/SSAP.1992.246792","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246792","url":null,"abstract":"In some DOA applications, the M sensors of the array can be affected by spatially uncorrelated white noise having power levels different from sensor to sensor. Such a noise power unbalance induces severe bias errors of DOA estimates performed by eigenspace based methods. In some instances, an estimate of the ratio between the noise variances of the sensors is available, so that a noise pre-compensation procedure can be conceived. For this purpose, a generalized AR estimator is considered in connection with the signal enhancement approach. Simulation examples illustrate the method.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129873911","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246779
S. V. Schell, W. Gardner
It is shown that cyclostationarity-exploiting direction-finding methods can be much less sensitive than conventional methods to errors in the array calibration data. In particular, when only a small subset of the signals arriving at the array exhibits the desired cyclostationarity property, the signal-selective methods can operate properly in the presence of calibration errors that cause the conventional methods to fail.<>
{"title":"Robustness of direction-finding methods for cyclostationary signals in the presence of array calibration error","authors":"S. V. Schell, W. Gardner","doi":"10.1109/SSAP.1992.246779","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246779","url":null,"abstract":"It is shown that cyclostationarity-exploiting direction-finding methods can be much less sensitive than conventional methods to errors in the array calibration data. In particular, when only a small subset of the signals arriving at the array exhibits the desired cyclostationarity property, the signal-selective methods can operate properly in the presence of calibration errors that cause the conventional methods to fail.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121154569","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246892
J. Xin, K. Nagasawa, A. Sano
The regularization in third-order cumulant-based parameter estimation is discussed for identification of transfer functions. The SVD-based regularization algorithm to estimate the number of sinusoids in the presence of colored Gaussian noise is given on a basis of fourth-order cumulant. A new MSE-like criterion for determining the optimal multiple adjustable parameters is given to decide the number of sinusoids by comparing these parameters with the singular values of the fourth-order cumulant-based Toeplitz matrix.<>
{"title":"Generalized regularization in cumulant-based parameter estimation","authors":"J. Xin, K. Nagasawa, A. Sano","doi":"10.1109/SSAP.1992.246892","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246892","url":null,"abstract":"The regularization in third-order cumulant-based parameter estimation is discussed for identification of transfer functions. The SVD-based regularization algorithm to estimate the number of sinusoids in the presence of colored Gaussian noise is given on a basis of fourth-order cumulant. A new MSE-like criterion for determining the optimal multiple adjustable parameters is given to decide the number of sinusoids by comparing these parameters with the singular values of the fourth-order cumulant-based Toeplitz matrix.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121487246","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246831
D.H. Brooks, A. Petropulu
The authors consider an unknown deterministic or nonGaussian nonwhite stochastic signal transmitted through two different unknown LTI mixed phase FIR systems with only noisy observations of the system outputs. The goal is to identify the systems and/or deconvolve the input, to within a magnitude factor and a time delay. The systems must have no zeros on the unit circle and satisfy other mild conditions on the mutual location of their zeros. Previous approaches have been iterative or assumed the input to be stochastic and white or well-separated from the channel impulse response in some sense. A new non-iterative solution is based on the observation that cepstra (calculated via higher order spectra) corresponding to two 'difference' systems which have zeros due to the minimum (or reflected maximum) phase part of the first system and poles due to the second system can be obtained. Via the group delay separated the 'difference' cepstra are into pole and zero parts and thereby the systems and/or signal are reconstructed.<>
{"title":"Non-iterative blind deconvolution of colored or deterministic signals using higher order cepstra and group delay","authors":"D.H. Brooks, A. Petropulu","doi":"10.1109/SSAP.1992.246831","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246831","url":null,"abstract":"The authors consider an unknown deterministic or nonGaussian nonwhite stochastic signal transmitted through two different unknown LTI mixed phase FIR systems with only noisy observations of the system outputs. The goal is to identify the systems and/or deconvolve the input, to within a magnitude factor and a time delay. The systems must have no zeros on the unit circle and satisfy other mild conditions on the mutual location of their zeros. Previous approaches have been iterative or assumed the input to be stochastic and white or well-separated from the channel impulse response in some sense. A new non-iterative solution is based on the observation that cepstra (calculated via higher order spectra) corresponding to two 'difference' systems which have zeros due to the minimum (or reflected maximum) phase part of the first system and poles due to the second system can be obtained. Via the group delay separated the 'difference' cepstra are into pole and zero parts and thereby the systems and/or signal are reconstructed.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122674368","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246781
J. A. Clark, M. Sartori
A finite difference approximation of the Helmholtz equation numerically integrated over a measurement surface can determine the acoustic field throughout an entire volume of a homogeneous region outside. This approach has been developed and implemented to study acoustic fields radiating from large immersed structures from pressure data measured over a generalized cylindrical measurement surface. The numerical algorithm is described, and simulation examples are presented. The results show pressure, velocity, and intensity distributions both in the evanescent wave region of the geometric nearfield and in the acoustic farfield.<>
{"title":"Numerical propagation of spatially distributed acoustic sources using the exterior Helmholtz integral equation","authors":"J. A. Clark, M. Sartori","doi":"10.1109/SSAP.1992.246781","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246781","url":null,"abstract":"A finite difference approximation of the Helmholtz equation numerically integrated over a measurement surface can determine the acoustic field throughout an entire volume of a homogeneous region outside. This approach has been developed and implemented to study acoustic fields radiating from large immersed structures from pressure data measured over a generalized cylindrical measurement surface. The numerical algorithm is described, and simulation examples are presented. The results show pressure, velocity, and intensity distributions both in the evanescent wave region of the geometric nearfield and in the acoustic farfield.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122513213","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246784
M. Allam, A.R. Moghaddamjoo
A new method for the estimation of the direction of arrival (DOA) of correlated wideband signals received by an array of sensors uses 2-D directive filtering in the time-space domain. This results in selecting bins at different frequencies from signals arriving from different directions. Since signals at different frequencies are uncorrelated, any spectral estimator can then be used to estimate the DOA.<>
{"title":"A new approach for wideband signal processing","authors":"M. Allam, A.R. Moghaddamjoo","doi":"10.1109/SSAP.1992.246784","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246784","url":null,"abstract":"A new method for the estimation of the direction of arrival (DOA) of correlated wideband signals received by an array of sensors uses 2-D directive filtering in the time-space domain. This results in selecting bins at different frequencies from signals arriving from different directions. Since signals at different frequencies are uncorrelated, any spectral estimator can then be used to estimate the DOA.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126660541","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246885
J. Li
This paper studies three polarization estimation techniques with a uniform linear array of crossed dipoles. All three may be used to compute the polarization estimates of impinging narrow-band electromagnetic plane waves. Statistical performance analysis of the estimators is provided for high signal-to-noise ratio. Numerical results are presented to compare the performance of the estimators and to compare theoretical analysis and Monte-Carlo simulation results.<>
{"title":"On polarization estimation using a polarization sensitive array","authors":"J. Li","doi":"10.1109/SSAP.1992.246885","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246885","url":null,"abstract":"This paper studies three polarization estimation techniques with a uniform linear array of crossed dipoles. All three may be used to compute the polarization estimates of impinging narrow-band electromagnetic plane waves. Statistical performance analysis of the estimators is provided for high signal-to-noise ratio. Numerical results are presented to compare the performance of the estimators and to compare theoretical analysis and Monte-Carlo simulation results.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"291 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123176178","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246847
Z. Faraj, M. Kahla, F. Castanie
The structure of the multilayer adaptive filter is similar to that of a multilayer perceptron with an input layer to which signal samples are presented, an output layer where the estimated signal is obtained, and one or more intermediate layers of nodes. This paper describes the multi-layer adaptive algorithm, and numerical examples illustrate its performances.<>
{"title":"Multi-layer adaptive filtering","authors":"Z. Faraj, M. Kahla, F. Castanie","doi":"10.1109/SSAP.1992.246847","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246847","url":null,"abstract":"The structure of the multilayer adaptive filter is similar to that of a multilayer perceptron with an input layer to which signal samples are presented, an output layer where the estimated signal is obtained, and one or more intermediate layers of nodes. This paper describes the multi-layer adaptive algorithm, and numerical examples illustrate its performances.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114820446","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246826
A. V. Dandawate, G. Giannakis
Novel algorithms are presented for nonparametric input/output identification of systems using kth-order cyclic-polyspectra at known cycles. Errors-in-variables models with generally cyclostationary inputs are considered. The proposed methods for k>or=3 are insensitive to contamination of both input and output data by even cyclostationary Gaussian noise of unknown covariance. Additional insensitivity to different types of input disturbances is delineated. Consistent and asymptotically normal sample cyclic-polyspectrum estimators are used for implementation, and simulations illustrate the proposed algorithms.<>
{"title":"Nonparametric identification of linear (almost) periodically time-varying systems using cyclic-polyspectra","authors":"A. V. Dandawate, G. Giannakis","doi":"10.1109/SSAP.1992.246826","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246826","url":null,"abstract":"Novel algorithms are presented for nonparametric input/output identification of systems using kth-order cyclic-polyspectra at known cycles. Errors-in-variables models with generally cyclostationary inputs are considered. The proposed methods for k>or=3 are insensitive to contamination of both input and output data by even cyclostationary Gaussian noise of unknown covariance. Additional insensitivity to different types of input disturbances is delineated. Consistent and asymptotically normal sample cyclic-polyspectrum estimators are used for implementation, and simulations illustrate the proposed algorithms.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116057499","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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