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[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics最新文献

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On the use of higher-order statistics for robust endpoint detection of speech 高阶统计量在语音鲁棒端点检测中的应用
[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics Pub Date : 1993-06-07 DOI: 10.1109/HOST.1993.264597
Maria Rangoussi, Anastasios Delopoulos, M. Tsatsanis
{"title":"On the use of higher-order statistics for robust endpoint detection of speech","authors":"Maria Rangoussi, Anastasios Delopoulos, M. Tsatsanis","doi":"10.1109/HOST.1993.264597","DOIUrl":"https://doi.org/10.1109/HOST.1993.264597","url":null,"abstract":"Third order statistics of speech signals are not identically zero, as it would be expected based on the linear model for voice. This is due to quadratic harmonic coupling produced in the vocal tract. Based on this observation, third order cumulants are employed to address the endpoint detection problem in low SNR level recordings due to their immunity to (colored) additive non-skewed noise. The proposed method uses the maximum singular value of an appropriately formed cumulant matrix to distinguish between voiced parts of the speech signal, and silence (noise). Adaptive implementations are also proposed, making this method computationally attractive. Results of batch and adaptive forms are presented for real and simulated data.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116063697","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: 14
Bicorrelation & bispectrum non parametric & parametric approaches 双相关和双谱非参数和参数方法
[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics Pub Date : 1993-06-07 DOI: 10.1109/HOST.1993.264584
P. Duvaut, T. Doligez, D. Garreau
{"title":"Bicorrelation & bispectrum non parametric & parametric approaches","authors":"P. Duvaut, T. Doligez, D. Garreau","doi":"10.1109/HOST.1993.264584","DOIUrl":"https://doi.org/10.1109/HOST.1993.264584","url":null,"abstract":"A new class of non-Gaussian processes is introduced. They are obtained by squaring Gaussian ARMA processes and are thus called QARMA processes. Theoretical properties of QARMA processes are derived in terms of their bicorrelation, bispectrum and bi-z-density. They happen to exhibit pertinent parameters on particular axes named hereafter principal axes. A lower bound of the variance of the bicorrelation estimate is derived based on a novel approach that makes use of Hermite polynomials. Its value is confirmed by simulation. Calibration abacusses giving the number of samples required by a specific accuracy are drawn. The effects of measurement samples, observation samples, smoothing and sample rate are taken into account. The robustness with respect to an additive (quantization included) or multiplicative noise is studied. The bicorrelogram obtained by the Fourier transform of the windowed bicorrelation is processed. Robustness and performance are studied.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122953546","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
An extended nonlinear transform domain adaptive filter 一种扩展的非线性变换域自适应滤波器
[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics Pub Date : 1993-06-07 DOI: 10.1109/HOST.1993.264602
M. U. Khurram, H. Ahmed
{"title":"An extended nonlinear transform domain adaptive filter","authors":"M. U. Khurram, H. Ahmed","doi":"10.1109/HOST.1993.264602","DOIUrl":"https://doi.org/10.1109/HOST.1993.264602","url":null,"abstract":"The concept of nonlinear transform domain adaptive filtering is extended to handle general inputs. Two solutions are proposed and a local temporal relationship is established between them. Layered implementation is shown to achieve performance comparable to the linear embedding solution with considerably reduced computations. Computer simulation shows improved learning performance compared to the LMS based structure driven with a non-Gaussian input.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125242756","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
Simultaneous DOA estimation based on Kolmogorov's theorem 基于Kolmogorov定理的同步DOA估计
[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics Pub Date : 1993-06-07 DOI: 10.1109/HOST.1993.264551
M. Nájar, M. Lagunas
{"title":"Simultaneous DOA estimation based on Kolmogorov's theorem","authors":"M. Nájar, M. Lagunas","doi":"10.1109/HOST.1993.264551","DOIUrl":"https://doi.org/10.1109/HOST.1993.264551","url":null,"abstract":"The design of a new architecture for signal processing, based on the Kolmogorov's theorem (1957), is addressed. This architecture is applied to solve the problem of source separation. Particularly, an adaptive algorithm is proposed to separate simultaneously all the unknown impinging sources on an aperture of sensors. The implemented framework is composed of two different stages: the first one is the inhibition stage, which turns the problem of estimating simultaneous DOAs (directions of arrival) into problems of a single source DOA estimation; and the second one is the optimisation stage which estimates the required parameter in a single signal context easier than the initial one with a multiple signal. A high order rule for learning is described, it improves the behaviour of the system assuring independence of the outputs.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125324139","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
Blind deconvolution of linear systems with nonstationary discrete inputs 非平稳离散输入线性系统的盲反卷积
[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics Pub Date : 1993-06-07 DOI: 10.1109/HOST.1993.264576
T.-H. Li
{"title":"Blind deconvolution of linear systems with nonstationary discrete inputs","authors":"T.-H. Li","doi":"10.1109/HOST.1993.264576","DOIUrl":"https://doi.org/10.1109/HOST.1993.264576","url":null,"abstract":"A method is proposed for blind deconvolution (equalization) of communication channels when their input signals are real- or complex-valued multilevel random sequences. The gist of the method is to apply a linear filter (equalizer) to the observed signal and to adjust it until a multilevel sequence is obtained from the output. It is shown that the problem can be solved with only scale/rotation and shift ambiguities. A cost function is proposed so that any minimizer of the function provides a solution to the problem. When the channel is parametric, a procedure is presented for the consistent estimation of the channel parameters. All these results are obtained for nonminimum phase linear systems without assuming the stationarity of the signal.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125337067","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
Applications of higher-order statistics to modelling, identification and cancellation of nonlinear distortion in high-speed samplers and analogue-to-digital converters using the Volterra and Wiener models 使用Volterra和Wiener模型的高阶统计量在高速采样器和模数转换器中建模、识别和消除非线性失真的应用
[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics Pub Date : 1993-06-07 DOI: 10.1109/HOST.1993.264531
J. Tsimbinos, K. Lever
{"title":"Applications of higher-order statistics to modelling, identification and cancellation of nonlinear distortion in high-speed samplers and analogue-to-digital converters using the Volterra and Wiener models","authors":"J. Tsimbinos, K. Lever","doi":"10.1109/HOST.1993.264531","DOIUrl":"https://doi.org/10.1109/HOST.1993.264531","url":null,"abstract":"The authors demonstrate the use of the Volterra and Wiener models for the identification and removal of low order (soft) nonlinear distortion in high speed analogue-to-digital converters. In particular, they show that the Volterra and Wiener models may be used to identify and remove low order distortion in a typical high speed flash or two-stage subranging type analogue-to-digital converter, in which the input signal dependent timing jitter in its sample-and-hold circuit is the dominant source of distortion. A fifth order Volterra model is used to represent the sampler's timing jitter distortion. They obtain the Volterra model kernels using either the Lee-Schetzen (1976, 1989) method and the relationship between the Wiener and Volterra kernels, or by using an adaptive method to obtain the Volterra kernels directly. They then use a fifth order Volterra inverse to apply post-distortion to compensate for the sampler distortion.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121895836","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: 55
Prefiltering for higher order advantage 高阶优势的预滤波
[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics Pub Date : 1993-06-07 DOI: 10.1109/HOST.1993.264546
G. Ioup, L. A. Pflug, J. Ioup, R. Field
{"title":"Prefiltering for higher order advantage","authors":"G. Ioup, L. A. Pflug, J. Ioup, R. Field","doi":"10.1109/HOST.1993.264546","DOIUrl":"https://doi.org/10.1109/HOST.1993.264546","url":null,"abstract":"Prefiltering, or limiting the spectral domain of data, improves maximum magnitude correlation peak detectors, both ordinary and higher order, for known and unknown sources. The only exception is the matched filter, which intrinsically contains prefiltering. For the cases studied, prefiltering generally has a higher order advantage, i.e., for higher order and in higher dimensions, it is even more effective than in one dimension for the ordinary correlation. Geometrical considerations can give some insight into this advantage. The tricorrelation detector with prefiltering performs best for all eight tested signals in the unknown source tests, and is the best detector for seven of the eight signals in the known source tests. Prefiltering for higher order correlation detectors involves only one-dimensional filtering and so is computationally efficient.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114364242","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: 8
New self-adaptative algorithms for source separation based on contrast functions 基于对比函数的源分离自适应新算法
[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics Pub Date : 1993-06-07 DOI: 10.1109/HOST.1993.264564
E. Moreau, O. Macchi
{"title":"New self-adaptative algorithms for source separation based on contrast functions","authors":"E. Moreau, O. Macchi","doi":"10.1109/HOST.1993.264564","DOIUrl":"https://doi.org/10.1109/HOST.1993.264564","url":null,"abstract":"Introduces self-adaptive algorithms for source separation based on a generalized criterion with the introduction of cross-cumulants. By adequate adaptive preprocessing it can be supposed that the observed source mixture x is 'white'. Then a separating matrix H (such that y=Hx has independent components) can be assumed unitary. A new contrast function is defined whose maximum occurs when H is separating. Its (simple) form admits an associated adaptive algorithm. Two different algorithms are proposed to estimate H, either directly or through its equivalent product of Givens rotations. Computer simulations illustrate the contribution of the cross-cumulants on the convergence of the algorithms. In the three-sources case, they show that the performances are improved substantially.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114621014","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: 105
The Wigner-Ville trispectrum: definition and application 维格纳-维尔三谱:定义与应用
[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics Pub Date : 1993-06-07 DOI: 10.1109/HOST.1993.264555
B. Boashash, Branko Ristich
{"title":"The Wigner-Ville trispectrum: definition and application","authors":"B. Boashash, Branko Ristich","doi":"10.1109/HOST.1993.264555","DOIUrl":"https://doi.org/10.1109/HOST.1993.264555","url":null,"abstract":"The Wigner-Ville trispectrum (WVT) is defined as a member of a class of time-varying higher-order spectra based on the polynomial Wigner-Ville distributions. It is shown that the WVT is a very efficient time-frequency analysis method for the analysis of FM signals affected by multiplicative noise, and outperforms the Wigner-Ville spectrum (WVS), and therefore any other method based on Cohen's class of bilinear time-frequency spectra. The authors further consider the instantaneous frequency estimator based on the peak extraction of the WVT. They also develop the statistical properties of such an estimator, for signals affected by both multiplicative and additive Gaussian noise.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129240282","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: 10
Blind deconvolution of non-linear random signals 非线性随机信号的盲反卷积
[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics Pub Date : 1993-06-07 DOI: 10.1109/HOST.1993.264566
A. Petropulu
{"title":"Blind deconvolution of non-linear random signals","authors":"A. Petropulu","doi":"10.1109/HOST.1993.264566","DOIUrl":"https://doi.org/10.1109/HOST.1993.264566","url":null,"abstract":"Presents a new nonparametric blind deconvolution algorithm for colored nonlinear random processes. A blind deconvolution algorithm reconstructs the input of an unknown linear time-invariant (LTI) system having access only to its output. A review of the existing blind deconvolution algorithms reveals that the schemes that require the least amount of knowledge about the input signal and the LTI system, were developed for white input signals, or rely on parametric modeling of both the system and the input. In order to develop nonparametric algorithms for the deconvolution of colored nonlinear processes of unknown statistics, one is forced to consider a two channel approach. The proposed algorithm utilizes the data collected by two different receivers, each being the output of a different system due to the same input. The two systems are then reconstructed combining higher-order statistics of the measured signals and the theory of signal reconstruction from higher-order spectral phase only.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130486913","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
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