É. Moulines, J. W. Dalle Molle, K. Choukri, M. Charbit
{"title":"Testing that a stationary time-series is Gaussian: time-domain vs. frequency-domain approaches","authors":"É. Moulines, J. W. Dalle Molle, K. Choukri, M. Charbit","doi":"10.1109/HOST.1993.264540","DOIUrl":"https://doi.org/10.1109/HOST.1993.264540","url":null,"abstract":"Several frequency-domain and time-domain procedures for testing that a stationary time-series are Gaussian are presented. Closed-form expressions of the asymptotic distribution of the test statistics under the null hypothesis of Gaussianity are derived. These procedures are then compared and assessed in two typical examples of applications (i) the detection of additive non-Gaussian outliers in stationary Gaussian noise with unknown covariance and (ii) the detection of the presence of contaminating values from non-symmetric distributions.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"6 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":"115400832","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}
{"title":"Utilization of orthogonal higher-order coherence functions for cubic Volterra model identification","authors":"S. Im, S.B. Kim, E. Powers","doi":"10.1109/HOST.1993.264585","DOIUrl":"https://doi.org/10.1109/HOST.1993.264585","url":null,"abstract":"Presents an approach to frequency-domain cubic Volterra kernel identification where the kernel has a limited number of significant frequency-domain coefficients (which are complex quantities). The orthogonal higher-order coherence functions are utilized to select the most significant frequency-domain Volterra kernel coefficients to be included in the cubic Volterra model. The practicality and feasibility of this approach is demonstrated by utilizing it to model actual physical nonlinear systems given experimental input-output data from such systems.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"41 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":"125543066","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}
{"title":"Ambiguity function, polynomial phase signals and higher-order cyclostationarity","authors":"S. Shamsunder, G. Giannakis","doi":"10.1109/HOST.1993.264573","DOIUrl":"https://doi.org/10.1109/HOST.1993.264573","url":null,"abstract":"By establishing a relationship between the classical ambiguity function and the sample cyclic cross correlation, it is shown that the former provides consistent estimates of delay and Doppler when the target echoes are observed in stationary noise. A novel fourth-order ambiguity function is proposed for estimating the delay and Doppler from random modulated Doppler-spread echoes. It is also shown that the conventional yields inconsistent estimates when the modulating process is zero-mean. Next, a method exploiting cyclostationarity of the signal is proposed for estimating the position and track of a generally maneuvering target or source. The received signal in this case can be modeled as a random amplitude polynomial phase process. Because of the statistical framework, the proposed approach also allows multiple signals, is theoretically insensitive to any stationary noise and provides a sequential estimation procedure.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"38 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":"127024703","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}
{"title":"Estimation for finite parameter schemes","authors":"K. Lii, M. Rosenblatt","doi":"10.1109/HOST.1993.264582","DOIUrl":"https://doi.org/10.1109/HOST.1993.264582","url":null,"abstract":"The object is to indicate the character of results for the approximate maximum likelihood estimation of parameters in nonminimum phase nonGaussian finite parameter schemes. The estimates are asymptotically normal under appropriate smoothness and positivity conditions on the probability density function of the generating independent random variables. The character of the asymptotic covariance matrix is indicated. In the truly nonminimum phase nonGaussian case one does not have consistency using the classical estimates using a Gaussian likelihood.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"26 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":"121971212","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}
{"title":"Velocity measurement of radar targets using HOS","authors":"R. D. Pierce","doi":"10.1109/HOST.1993.264575","DOIUrl":"https://doi.org/10.1109/HOST.1993.264575","url":null,"abstract":"The application of higher-order statistics (HOS) to velocity measurements of radar targets takes advantage of the HOS characteristic that fourth-order estimators can be unbiased by Gaussian noise. Using data from a stepped-frequency, coherent radar, the samples are coherently averaged in the trispectrum or in slices of the trispectrum. The ratio of the averages produces a transfer function where phase is related to velocity. The HOS method is compared to a classical, second order method similar to cross-spectrum analysis. An example using real radar data shows a case where the classical method does not work.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"55 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":"129843505","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}
{"title":"Texture synthesis using asymmetric 2-D noncausal AR models","authors":"Jitendra Tugnait","doi":"10.1109/HOST.1993.264594","DOIUrl":"https://doi.org/10.1109/HOST.1993.264594","url":null,"abstract":"The author investigates the suitability of two-dimensional (2-D), noncausal, autoregressive (AR) models with possibly asymmetric support for synthesis of images visually similar to natural textures. These models characterize the gray level at an image pixel as a linear combination of gray levels at nearby locations in all directions and an additive non-Gaussian, higher-order white noise variable. Existing results based upon the second-order statistics of the images assume that the model support is symmetric, whereas the author exploits higher-order statistics of the image to fit AR models with possibly asymmetric support. Experimental results of synthesis of 128*128 textures visually resembling several real life textures in the Brodatz album (and other sources) are presented. The synthetic textures are generated using models obtained from real images via inverse filter criteria.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"31 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":"126970000","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}
{"title":"Hybrid lattice: an efficient nonlinear lattice structure","authors":"M. U. Khurram, H. Ahmed","doi":"10.1109/HOST.1993.264583","DOIUrl":"https://doi.org/10.1109/HOST.1993.264583","url":null,"abstract":"A true nonlinear lattice structure is presented which achieves temporal as well as spatial decorrelation. The interstage decorrelation is obtained through the adaptive lattice filter while the interchannel decorrelation is obtained through the escalator structure. This hybrid structure implements generalized Gram-Shmidt more efficiently than the multichannel escalator filter.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"14 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":"131421248","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}
{"title":"Study and simulation of sea clutter","authors":"I. Moreau","doi":"10.1109/HOST.1993.264572","DOIUrl":"https://doi.org/10.1109/HOST.1993.264572","url":null,"abstract":"Modeling sea clutter of high resolution maritime surveillance radar must provide a validation of algorithms in a perfect well-known context, before comparison with real data. The purpose of the paper is to study modelling of the sea clutter. It considers the temporal evolution of sea clutter for which statistical analysis is carried out. High order statistics are used to solve the problem. It also deals with spatial correlation of sea clutter.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"64 2 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":"133869737","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}
{"title":"Statistical monitoring of rotating machinery by cumulant spectral analysis","authors":"R. W. Barker, M. Hinich","doi":"10.1109/HOST.1993.264570","DOIUrl":"https://doi.org/10.1109/HOST.1993.264570","url":null,"abstract":"A higher-order statistical (HOS) signature analysis methodology was applied to accelerometer data from a drilling machine collected in a controlled experiment drilling holes through composite circuit panels. Background on the drill wear monitoring problem including approaches using a combination of sensors and signal features are briefly summarized. Experiment results reveal that statistics from the second order cumulant spectrum not constrained to the periodic component support set had increased discrimination power when studying early or incipient drill wear. Detailed classification results show that feature sets composed of second order cumulant components had greater sensitivity than bispectrum and power spectrum features for indicating incipient drill wear.<<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":"131211095","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}
{"title":"Antenna array noise reconditioning by cumulants","authors":"M. Dogan, J. Mendel","doi":"10.1109/HOST.1993.264563","DOIUrl":"https://doi.org/10.1109/HOST.1993.264563","url":null,"abstract":"The main motivation of using higher order statistics in signal processing applications has been their insensitivity to additive colored Gaussian noise. The main objection to those methods is their vulnerability to nonGaussian noise. The authors first give an interpretation for the information provided by cumulants for array processing applications. Then, they investigate the possibility of suppressing the effects of nonGaussian noise. It is shown that existing arrays can be reconditioned by an additional sensor and by using cumulants. It is also shown that existing cumulant-based algorithms are less sensitive to colored nonGaussian noise than their covariance-based counterparts above a threshold SNR.<<ETX>>","PeriodicalId":439030,"journal":{"name":"[1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"53 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":"115872851","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}