Download or read book Blind and Semi Blind Signal Processing written by Vicente Zarzoso and published by LAP Lambert Academic Publishing. This book was released on 2010 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: The estimation of source signals from observations corrupted by noise and interference is a fundamental signal processing problem arising in a wide variety of real-life applications. Blind techniques, including blind source separation and independent component analysis, have become very popular over the last decades, but they also present important drawbacks such as estimation ambiguities, local extrema, high complexity and slow convergence. This work summarizes the Author s results on novel signal estimation techniques alleviating the shortcomings of the blind approach. Emphasis is laid on two specific applications in telecommunications and biomedical signal processing: equalization and source separation in digital communication channels, and atrial activity extraction in atrial fibrillation, the most common cardiac arrhythmia. Most of the proposed techniques can be considered as semi-blind in that they aim to exploit available prior information about the problems under study. The book concludes by highlighting some future challenges in these topics. This work is addressed to researchers and engineers interested in signal processing for communications and biomedical problems.

Download or read book Blind Signal Processing written by Xizhi Shi and published by Springer Science & Business Media. This book was released on 2011-12-28 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Blind Signal Processing: Theory and Practice" not only introduces related fundamental mathematics, but also reflects the numerous advances in the field, such as probability density estimation-based processing algorithms, underdetermined models, complex value methods, uncertainty of order in the separation of convolutive mixtures in frequency domains, and feature extraction using Independent Component Analysis (ICA). At the end of the book, results from a study conducted at Shanghai Jiao Tong University in the areas of speech signal processing, underwater signals, image feature extraction, data compression, and the like are discussed. This book will be of particular interest to advanced undergraduate students, graduate students, university instructors and research scientists in related disciplines. Xizhi Shi is a Professor at Shanghai Jiao Tong University.

Download or read book Blind Source Separation written by Xianchuan Yu and published by John Wiley & Sons. This book was released on 2013-12-13 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies The book presents an overview of Blind Source Separation, a relatively new signal processing method. Due to the multidisciplinary nature of the subject, the book has been written so as to appeal to an audience from very different backgrounds. Basic mathematical skills (e.g. on matrix algebra and foundations of probability theory) are essential in order to understand the algorithms, although the book is written in an introductory, accessible style. This book offers a general overview of the basics of Blind Source Separation, important solutions and algorithms, and in-depth coverage of applications in image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition fMRI medical image processing, geochemical and geophysical data mining, mineral resources prediction and geoanomalies information recognition. Firstly, the background and theory basics of blind source separation are introduced, which provides the foundation for the following work. Matrix operation, foundations of probability theory and information theory basics are included here. There follows the fundamental mathematical model and fairly new but relatively established blind source separation algorithms, such as Independent Component Analysis (ICA) and its improved algorithms (Fast ICA, Maximum Likelihood ICA, Overcomplete ICA, Kernel ICA, Flexible ICA, Non-negative ICA, Constrained ICA, Optimised ICA). The last part of the book considers the very recent algorithms in BSS e.g. Sparse Component Analysis (SCA) and Non-negative Matrix Factorization (NMF). Meanwhile, in-depth cases are presented for each algorithm in order to help the reader understand the algorithm and its application field. A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies Presents new improved algorithms aimed at different applications, such as image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition, and MRI medical image processing With applications in geochemical and geophysical data mining, mineral resources prediction and geoanomalies information recognition Written by an expert team with accredited innovations in blind source separation and its applications in natural science Accompanying website includes a software system providing codes for most of the algorithms mentioned in the book, enhancing the learning experience Essential reading for postgraduate students and researchers engaged in the area of signal processing, data mining, image processing and recognition, information, geosciences, life sciences.

Download or read book Adaptive Blind Signal and Image Processing written by Andrzej Cichocki and published by John Wiley & Sons. This book was released on 2002-06-14 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Im Mittelpunkt dieses modernen und spezialisierten Bandes stehen adaptive Strukturen und unüberwachte Lernalgorithmen, besonders im Hinblick auf effektive Computersimulationsprogramme. Anschauliche Illustrationen und viele Beispiele sowie eine interaktive CD-ROM ergänzen den Text.

Download or read book Handbook of Blind Source Separation written by Pierre Comon and published by Academic Press. This book was released on 2010-02-17 with total page 856 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edited by the people who were forerunners in creating the field, together with contributions from 34 leading international experts, this handbook provides the definitive reference on Blind Source Separation, giving a broad and comprehensive description of all the core principles and methods, numerical algorithms and major applications in the fields of telecommunications, biomedical engineering and audio, acoustic and speech processing. Going beyond a machine learning perspective, the book reflects recent results in signal processing and numerical analysis, and includes topics such as optimization criteria, mathematical tools, the design of numerical algorithms, convolutive mixtures, and time frequency approaches. This Handbook is an ideal reference for university researchers, R&D engineers and graduates wishing to learn the core principles, methods, algorithms, and applications of Blind Source Separation. Covers the principles and major techniques and methods in one book Edited by the pioneers in the field with contributions from 34 of the world’s experts Describes the main existing numerical algorithms and gives practical advice on their design Covers the latest cutting edge topics: second order methods; algebraic identification of under-determined mixtures, time-frequency methods, Bayesian approaches, blind identification under non negativity approaches, semi-blind methods for communications Shows the applications of the methods to key application areas such as telecommunications, biomedical engineering, speech, acoustic, audio and music processing, while also giving a general method for developing applications

Download or read book Independent Component Analysis and Blind Signal Separation written by Justinian Rosca and published by Springer. This book was released on 2006-02-27 with total page 1000 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Independent Component Analysis and Blind Source Separation, ICA 2006, held in Charleston, SC, USA, in March 2006. The 120 revised papers presented were carefully reviewed and selected from 183 submissions. The papers are organized in topical sections on algorithms and architectures, applications, medical applications, speech and signal processing, theory, and visual and sensory processing.

Download or read book Blind Equalization and Identification written by Zhi Ding and published by CRC Press. This book was released on 2018-10-08 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text seeks to clarify various contradictory claims regarding capabilities and limitations of blind equalization. It highlights basic operating conditions and potential for malfunction. The authors also address concepts and principles of blind algorithms for single input multiple output (SIMO) systems and multi-user extensions of SIMO equalization and identification.

Download or read book Blind Source Separation written by Ganesh R. Naik and published by Springer. This book was released on 2014-05-21 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Blind Source Separation intends to report the new results of the efforts on the study of Blind Source Separation (BSS). The book collects novel research ideas and some training in BSS, independent component analysis (ICA), artificial intelligence and signal processing applications. Furthermore, the research results previously scattered in many journals and conferences worldwide are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers, R&D engineers and graduate students in computer science and electronics who wish to learn the core principles, methods, algorithms and applications of BSS. Dr. Ganesh R. Naik works at University of Technology, Sydney, Australia; Dr. Wenwu Wang works at University of Surrey, UK.

Download or read book Blind Identification and Separation of Complex valued Signals written by Eric Moreau and published by John Wiley & Sons. This book was released on 2013-10-07 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Blind identification consists of estimating a multi-dimensional system only through the use of its output, and source separation, the blind estimation of the inverse of the system. Estimation is generally carried out using different statistics of the output. The authors of this book consider the blind identification and source separation problem in the complex-domain, where the available statistical properties are richer and include non-circularity of the sources – underlying components. They define identifiability conditions and present state-of-the-art algorithms that are based on algebraic methods as well as iterative algorithms based on maximum likelihood theory. Contents 1. Mathematical Preliminaries. 2. Estimation by Joint Diagonalization. 3. Maximum Likelihood ICA. About the Authors Eric Moreau is Professor of Electrical Engineering at the University of Toulon, France. His research interests concern statistical signal processing, high order statistics and matrix/tensor decompositions with applications to data analysis, telecommunications and radar. Tülay Adali is Professor of Electrical Engineering and Director of the Machine Learning for Signal Processing Laboratory at the University of Maryland, Baltimore County, USA. Her research interests concern statistical and adaptive signal processing, with an emphasis on nonlinear and complex-valued signal processing, and applications in biomedical data analysis and communications. Blind identification consists of estimating a multidimensional system through the use of only its output. Source separation is concerned with the blind estimation of the inverse of the system. The estimation is generally performed by using different statistics of the outputs. The authors consider the blind estimation of a multiple input/multiple output (MIMO) system that mixes a number of underlying signals of interest called sources. They also consider the case of direct estimation of the inverse system for the purpose of source separation. They then describe the estimation theory associated with the identifiability conditions and dedicated algebraic algorithms. The algorithms depend critically on (statistical and/or time frequency) properties of complex sources that will be precisely described.

Download or read book Advances in Modern Blind Signal Separation Algorithms written by Kostas Kokkinakis and published by Springer Nature. This book was released on 2022-06-01 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: With human-computer interactions and hands-free communications becoming overwhelmingly important in the new millennium, recent research efforts have been increasingly focusing on state-of-the-art multi-microphone signal processing solutions to improve speech intelligibility in adverse environments. One such prominent statistical signal processing technique is blind signal separation (BSS). BSS was first introduced in the early 1990s and quickly emerged as an area of intense research activity showing huge potential in numerous applications. BSS comprises the task of 'blindly' recovering a set of unknown signals, the so-called sources from their observed mixtures, based on very little to almost no prior knowledge about the source characteristics or the mixing structure. The goal of BSS is to process multi-sensory observations of an inaccessible set of signals in a manner that reveals their individual (and original) form, by exploiting the spatial and temporal diversity, readily accessible through a multi-microphone configuration. Proceeding blindly exhibits a number of advantages, since assumptions about the room configuration and the source-to-sensor geometry can be relaxed without affecting overall efficiency. This booklet investigates one of the most commercially attractive applications of BSS, which is the simultaneous recovery of signals inside a reverberant (naturally echoing) environment, using two (or more) microphones. In this paradigm, each microphone captures not only the direct contributions from each source, but also several reflected copies of the original signals at different propagation delays. These recordings are referred to as the convolutive mixtures of the original sources. The goal of this booklet in the lecture series is to provide insight on recent advances in algorithms, which are ideally suited for blind signal separation of convolutive speech mixtures. More importantly, specific emphasis is given in practical applications of the developed BSS algorithms associated with real-life scenarios. The developed algorithms are put in the context of modern DSP devices, such as hearing aids and cochlear implants, where design requirements dictate low power consumption and call for portability and compact size. Along these lines, this booklet focuses on modern BSS algorithms which address (1) the limited amount of processing power and (2) the small number of microphones available to the end-user. Table of Contents: Fundamentals of blind signal separation / Modern blind signal separation algorithms / Application of blind signal processing strategies to noise reduction for the hearing-impaired / Conclusions and future challenges / Bibliography

Download or read book Independent Component Analysis and Blind Signal Separation written by Justinian Rosca and published by Springer. This book was released on 2006-02-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Independent Component Analysis and Blind Source Separation, ICA 2006, held in Charleston, SC, USA, in March 2006. The 120 revised papers presented were carefully reviewed and selected from 183 submissions. The papers are organized in topical sections on algorithms and architectures, applications, medical applications, speech and signal processing, theory, and visual and sensory processing.

Download or read book Implementing Blind Source Separation in Signal Processing and Telecommunications written by Wai Yie Leong and published by . This book was released on 2005 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book New Algorithms for Blind Equalization and Blind Source Separation phase Recovery written by Trasapong Thaiupathump and published by . This book was released on 2002 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Independent Component Analysis and Blind Signal Separation written by and published by . This book was released on 2004 with total page 1308 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Independent Component Analysis and Blind Signal Separation written by Carlos G. Puntonet and published by Springer Science & Business Media. This book was released on 2004-09-17 with total page 1304 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many situations found both in Nature and in human-built systems, a set of mixed signalsisobserved(frequentlyalsowithnoise),anditisofgreatscienti?candtech- logicalrelevanceto beableto isolateor separatethemso thattheinformationin each ofthesignalscanbeutilized. Blind source separation (BSS) research is one of the more interesting emerging ?eldsnowadaysinthe?eldofsignalprocessing.Itdealswiththealgorithmsthatallow therecoveryoftheoriginalsourcesfromasetofmixturesonly.Theadjective"blind" is applied becausethe purposeis to estimate the originalsourceswithoutany a priori knowledgeabouteitherthesourcesorthemixingsystem.Mostofthemodelsemployed in BSS assume the hypothesisabout the independenceof the original sources. Under this hypothesis,a BSS problemcan be consideredas a particularcase of independent componentanalysis(ICA),alineartransformationtechniquethat,startingfromam- tivariate representation of the data, minimizes the statistical dependence between the componentsoftherepresentation.Itcan beclaimed thatmostoftheadvancesin ICA havebeenmotivatedbythesearchforsolutionstotheBSSproblemand,theotherway around,advancesinICAhavebeenimmediatelyappliedtoBSS. ICA and BSS algorithms start from a mixture model, whose parameters are - timated from the observed mixtures. Separation is achieved by applying the inverse mixturemodelto theobservedsignals(separatingorunmixingmodel).Mixturem- els usually fall into three broad categories: instantaneous linear models, convolutive modelsandnonlinearmodels,the?rstonebeingthesimplestbut,in general,notnear realisticapplications.Thedevelopmentandtestofthealgorithmscanbeaccomplished throughsyntheticdataorwithreal-worlddata.Obviously,themostimportantaim(and mostdif?cult)istheseparationofreal-worldmixtures.BSSandICAhavestrongre- tionsalso,apartfromsignalprocessing,withother?eldssuchasstatisticsandarti?cial neuralnetworks. As long as we can ?nd a system that emits signals propagated through a mean, andthosesignalsarereceivedbyasetofsensorsandthereisaninterestinrecovering the originalsources,we have a potential?eld ofapplication forBSS and ICA. Inside thatwiderangeofapplicationswecan?nd,forinstance:noisereductionapplications, biomedicalapplications,audiosystems,telecommunications,andmanyothers. This volume comes out just 20 years after the ?rst contributionsin ICA and BSS 1 appeared . Thereinafter,the numberof research groupsworking in ICA and BSS has been constantly growing, so that nowadays we can estimate that far more than 100 groupsareresearchinginthese?elds. Asproofoftherecognitionamongthescienti?ccommunityofICAandBSSdev- opmentstherehavebeennumerousspecialsessionsandspecialissuesinseveralwell- 1 J.Herault, B.Ans,"Circuits neuronaux à synapses modi?ables: décodage de messages c- posites para apprentissage non supervise", C.R. de l'Académie des Sciences, vol. 299, no. III-13,pp.525-528,1984.

Download or read book Signal Processing for Wireless Communication Systems written by H. Vincent Poor and published by Springer Science & Business Media. This book was released on 2006-01-19 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal Processing for Wireless Communication Systems brings together in one place important contributions and up-to-date research results in this fast moving area. The Contributors to this work were selected from leading researchers and practitioners in this field. The book's 18 chapters are divided into three areas: systems, Networks, and Implementation Issues; Channel Estimation and Equalization; and Multiuser Detection. The Work, originally published as Volume 30, Numbers 1-3 of the Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, will be valuable to anyone working or researching in the field of wireless communication systems. It serves as an excellent reference, providing insight into some of the most challenging issues being examined today.

Download or read book The Whole Story Behind Blind Adaptive Equalizers Blind Deconvolution written by Monika Pinchas and published by Bentham Science Publishers. This book was released on 2012 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is well known that Intersymbol (ISI) Interference is a limiting factor in many communication environments where it causes an irreducible degradation of the bit error rate (BER) thus imposing an upper limit on the data symbol rate. In order to overcome the ISI problem, an equalizer is implemented in those systems. Among the three types of equalizers - non-blind, semi-blind and blind - the blind equalizer has the benefit of bandwidth saving and there is no need of going through a training phase. Blind equalization algorithms are essentially adaptive filtering algorithms designed such that they do not require the external supply of a desired response to generate the error signal in the output of the adaptive equalization filter. the algorithms generate an estimate of the desired response by applying a nonlinear transformation to sequences involved in the adaptation process. This nonlinearity is designed to minimize a cost function that is implicitly based on higher order statistics (HOS) according to one approach, or calculated directly according to the Bayes rules. The Whole Story behind Blind Adaptive Equalizers/ Blind Deconvolution gives the readers a full understanding on the blind deconvolution. the e-book covers a variety of blind deconvolution/equalization methods based on both cost functions and Bayes rules where simulation results are supplied to support the theory. These include the Maximum Entropy density approximation technique and the Edgeworth Expansion approach used in various blind equalizers. It also describes the relationship between the cost function approach and the approach taken according to Bayes rules. the e-book deals also with the effect of various system parameters (such as the step-size parameter or the equalizer's tap length) have on the obtained equalization performance. This e-book will be of particular interest to advanced communications engineering undergraduate students, graduate students, university instructors and signal processing researchers.