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Fifth ASSP Workshop on Spectrum Estimation and Modeling最新文献

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Bilinear time series in non-Gaussian signal modeling 非高斯信号建模中的双线性时间序列
Fifth ASSP Workshop on Spectrum Estimation and Modeling Pub Date : 1900-01-01 DOI: 10.1109/SPECT.1990.205536
H. M. Valenzuela, N. Bose
{"title":"Bilinear time series in non-Gaussian signal modeling","authors":"H. M. Valenzuela, N. Bose","doi":"10.1109/SPECT.1990.205536","DOIUrl":"https://doi.org/10.1109/SPECT.1990.205536","url":null,"abstract":"Non-Gaussian processes are taken to be the output of a bilinear system driven by a Gaussian white noise. The authors develop a 2D quarter-plane bilinear model as a nontrivial generalization of a 1D bilinear time series model. A maximum-likelihood-based parameter estimation method is then developed. Finally, the validity of the model is illustrated by simulation examples.<<ETX>>","PeriodicalId":117661,"journal":{"name":"Fifth ASSP Workshop on Spectrum Estimation and Modeling","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121023480","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}
引用次数: 2
Suppression of interference terms in Wigner distribution by median filtering 用中值滤波抑制Wigner分布中的干扰项
Fifth ASSP Workshop on Spectrum Estimation and Modeling Pub Date : 1900-01-01 DOI: 10.1109/SPECT.1990.205597
H. Oung, J. Reid
{"title":"Suppression of interference terms in Wigner distribution by median filtering","authors":"H. Oung, J. Reid","doi":"10.1109/SPECT.1990.205597","DOIUrl":"https://doi.org/10.1109/SPECT.1990.205597","url":null,"abstract":"The Wigner distributions is known to have interfering cross-terms when applied to a multicomponent signal. Linear filtering techniques have been applied to suppress the interference but result in smearing of the time-frequency distribution. A nonlinear filtering technique is proposed that suppresses the interference without smearing the distribution. The technique consists of the median filtering of the cumulative distribution function and its performance is studied with computer simulated data. Good results were obtained even for a long data window.<<ETX>>","PeriodicalId":117661,"journal":{"name":"Fifth ASSP Workshop on Spectrum Estimation and Modeling","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121026641","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}
引用次数: 1
Adaptive deconvolution and system identification using higher order moments 基于高阶矩的自适应反卷积和系统辨识
Fifth ASSP Workshop on Spectrum Estimation and Modeling Pub Date : 1900-01-01 DOI: 10.1109/SPECT.1990.205576
N. Rozario, A. Papoulis
{"title":"Adaptive deconvolution and system identification using higher order moments","authors":"N. Rozario, A. Papoulis","doi":"10.1109/SPECT.1990.205576","DOIUrl":"https://doi.org/10.1109/SPECT.1990.205576","url":null,"abstract":"Introduces a new method to adaptively deconvolve a linear process. The problem is to obtain the unknown linear system and the underlying white-noise process in a simple adaptive manner. The solution is based on second and higher order moments, and is exceedingly easy to implement. The method is radically different from the familiar gradient-based schemes used in adaptive filtering.<<ETX>>","PeriodicalId":117661,"journal":{"name":"Fifth ASSP Workshop on Spectrum Estimation and Modeling","volume":"265 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133287107","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}
引用次数: 1
The MAP method of estimating the directions of signals in unknown correlated noise 在未知相关噪声下估计信号方向的MAP方法
Fifth ASSP Workshop on Spectrum Estimation and Modeling Pub Date : 1900-01-01 DOI: 10.1109/SPECT.1990.205604
K. Wong, J. Reilly, S. Qiao
{"title":"The MAP method of estimating the directions of signals in unknown correlated noise","authors":"K. Wong, J. Reilly, S. Qiao","doi":"10.1109/SPECT.1990.205604","DOIUrl":"https://doi.org/10.1109/SPECT.1990.205604","url":null,"abstract":"It is shown that the MAP (maximum a posteriori) approach, especially in view of possible parallel implementation, is a very attractive method of estimating the DOA (direction of arrival) of signals in unknown correlated noise.<<ETX>>","PeriodicalId":117661,"journal":{"name":"Fifth ASSP Workshop on Spectrum Estimation and Modeling","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115420683","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}
引用次数: 0
Spectrum estimation techniques to study quantization in A&D conversion systems 频谱估计技术研究的量化在A&D转换系统
Fifth ASSP Workshop on Spectrum Estimation and Modeling Pub Date : 1900-01-01 DOI: 10.1109/SPECT.1990.205573
A. Gandelli
{"title":"Spectrum estimation techniques to study quantization in A&D conversion systems","authors":"A. Gandelli","doi":"10.1109/SPECT.1990.205573","DOIUrl":"https://doi.org/10.1109/SPECT.1990.205573","url":null,"abstract":"Presents an innovative theory based on the distribution theory and spectrum estimation techniques to investigate the in-depth properties of the transfer function of analog-to-digital converters and therefore, essentially, to provide a theoretical approach at the quantization effect.<<ETX>>","PeriodicalId":117661,"journal":{"name":"Fifth ASSP Workshop on Spectrum Estimation and Modeling","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124595839","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}
引用次数: 1
Fractional moment spectra and related results 分数矩谱及其相关结果
Fifth ASSP Workshop on Spectrum Estimation and Modeling Pub Date : 1900-01-01 DOI: 10.1109/SPECT.1990.205537
A. Swami, J. Mendel
{"title":"Fractional moment spectra and related results","authors":"A. Swami, J. Mendel","doi":"10.1109/SPECT.1990.205537","DOIUrl":"https://doi.org/10.1109/SPECT.1990.205537","url":null,"abstract":"The authors consider the following problems: (a) What is the p.d.f. with maximum entropy subject to cumulant constraints? (b) Given that a signal consists of two harmonics of unknown frequencies, how can they determine whether both the harmonics are phase-coupled to another unobservable harmonic whose frequency is unknown? (c) When is it inappropriate to use cumulants in transient analysis and related problems where the signal is deterministic?.<<ETX>>","PeriodicalId":117661,"journal":{"name":"Fifth ASSP Workshop on Spectrum Estimation and Modeling","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126355925","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}
引用次数: 5
The peak of a causal signal with a given average delay 具有给定平均延迟的因果信号的峰值
Fifth ASSP Workshop on Spectrum Estimation and Modeling Pub Date : 1900-01-01 DOI: 10.1109/SPECT.1990.205584
J. Makhoul, A. Steinhardt
{"title":"The peak of a causal signal with a given average delay","authors":"J. Makhoul, A. Steinhardt","doi":"10.1109/SPECT.1990.205584","DOIUrl":"https://doi.org/10.1109/SPECT.1990.205584","url":null,"abstract":"Derives two results concerning the peak of a causal signal with a given average delay. The first result is that, for an average delay of tau , the maximum possible location of the signal peak is of the order of tau ( tau +3)/2. (This bound can also be interpreted as providing the maximum integer at which the most probable value of a discrete nonnegative random variable could occur, given that the random variable has a known mean.) The second result is that the signals that minimize the peak amplitude, subject to unit energy and average delay tau , have a peak value of the order of 1/ square root 2 tau +1. The authors construct causal signals for which the derived bounds are attained for any given real-valued delay. They also compare the derived bounds to the corresponding ones for all-pass signals.<<ETX>>","PeriodicalId":117661,"journal":{"name":"Fifth ASSP Workshop on Spectrum Estimation and Modeling","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116789620","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}
引用次数: 0
Local angular spectrum analysis of 2D signals 二维信号的局部角谱分析
Fifth ASSP Workshop on Spectrum Estimation and Modeling Pub Date : 1900-01-01 DOI: 10.1109/SPECT.1990.205545
G. Jacovitti, R. Cusani
{"title":"Local angular spectrum analysis of 2D signals","authors":"G. Jacovitti, R. Cusani","doi":"10.1109/SPECT.1990.205545","DOIUrl":"https://doi.org/10.1109/SPECT.1990.205545","url":null,"abstract":"A new local spectral characterization of 2D signals based on multichannel filter analysis is presented. The class of the employed functions, called harmonic angular (HA) filters, is derived from the concept of radial projections of local polar maps of the image. HA filters perform harmonic decomposition in an angular sense, rather than in the conventional orthogonal reference of the Gabor or wavelet approaches. This allows spectral and positional characterization of the most important image features such as edges, lines, corners, textures, etc. After a survey of the theoretical framework, the application to textured fields analysis is illustrated in some detail.<<ETX>>","PeriodicalId":117661,"journal":{"name":"Fifth ASSP Workshop on Spectrum Estimation and Modeling","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132786891","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}
引用次数: 4
Sinusoidal frequency estimation by approximate MUSIC method 用近似MUSIC方法估计正弦频率
Fifth ASSP Workshop on Spectrum Estimation and Modeling Pub Date : 1900-01-01 DOI: 10.1109/SPECT.1990.205603
J. Karhunen, J. Joutsensalo
{"title":"Sinusoidal frequency estimation by approximate MUSIC method","authors":"J. Karhunen, J. Joutsensalo","doi":"10.1109/SPECT.1990.205603","DOIUrl":"https://doi.org/10.1109/SPECT.1990.205603","url":null,"abstract":"Two efficient methods avoiding eigenvector computation are proposed for approximating the signal subspace in terms of the Fourier transform. The resulting approximations are used to substitute for the signal eigenvectors in MUSIC. The proposed methods perform almost the same as MUSIC at high SNRs and provide often clearly better results at low SNRs. They seem to be more robust than MUSIC against overestimation of the number of sinusoids.<<ETX>>","PeriodicalId":117661,"journal":{"name":"Fifth ASSP Workshop on Spectrum Estimation and Modeling","volume":"267 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122554813","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}
引用次数: 3
The spectral parameter estimation by using prefiltering and matrix pencil method 采用预滤波和矩阵笔法对光谱参数进行估计
Fifth ASSP Workshop on Spectrum Estimation and Modeling Pub Date : 1900-01-01 DOI: 10.1109/SPECT.1990.205543
F. Hu, T. Sarkar, Y. Hua
{"title":"The spectral parameter estimation by using prefiltering and matrix pencil method","authors":"F. Hu, T. Sarkar, Y. Hua","doi":"10.1109/SPECT.1990.205543","DOIUrl":"https://doi.org/10.1109/SPECT.1990.205543","url":null,"abstract":"A new approach called the band-pass matrix pencil (BPMP) method for estimating the parameters of exponentially damped or undamped sinusoidal signals is developed. The signal-to-noise ratio (SNR) can be enhanced by using the prefiltering process when prior information about the approximate location and the bandwidth of the signal is available. This information can be obtained by checking the periodogram of the signal. The matrix pencil (MP) method is then applied to the filtered data to estimate frequencies and damping factors of sinusoidal signals. The prefiltering process is not trivial, therefore, the approach presented utilizes the backward process for the IIR filtering and circular convolution for the FIR filtering. Monte Carlo simulations are used to illustrate the performance of the proposed estimation procedure.<<ETX>>","PeriodicalId":117661,"journal":{"name":"Fifth ASSP Workshop on Spectrum Estimation and Modeling","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127687921","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}
引用次数: 7
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