Handbook of Blind Source Separation

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  • Author : Pierre Comon
  • Publisher : Academic Press
  • Pages : 856 pages
  • ISBN : 9780080884943
  • Rating : 5/5 from 1 reviews
CLICK HERE TO GET THIS BOOK >>>Handbook of Blind Source Separation

Download or Read online Handbook of Blind Source Separation full in PDF, ePub and kindle. this book written by Pierre Comon and published by Academic Press which was released on 17 February 2010 with total page 856 pages. We cannot guarantee that Handbook of Blind Source Separation book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Handbook of Blind Source Separation

Handbook of Blind Source Separation
  • Author : Pierre Comon,Christian Jutten
  • Publisher : Academic Press
  • Release : 17 February 2010
GET THIS BOOK Handbook of Blind Source Separation

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

Blind Source Separation

Blind Source Separation
  • Author : Ganesh R. Naik,Wenwu Wang
  • Publisher : Springer
  • Release : 21 May 2014
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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

Blind Source Separation

Blind Source Separation
  • Author : Xianchuan Yu,Dan Hu,Jindong Xu
  • Publisher : John Wiley & Sons
  • Release : 13 December 2013
GET THIS BOOK Blind Source Separation

A systematic exploration of both classic and contemporaryalgorithms in blind source separation with practical casestudies The book presents an overview of Blind Source Separation, arelatively new signal processing method. Due to themultidisciplinary nature of the subject, the book has been writtenso as to appeal to an audience from very different backgrounds.Basic mathematical skills (e.g. on matrix algebra and foundationsof probability theory) are essential in order to understand thealgorithms, although the book is written in an introductory,accessible style.

Blind Source Separation

Blind Source Separation
  • Author : Yong Xiang,Dezhong Peng,Zuyuan Yang
  • Publisher : Springer
  • Release : 16 September 2014
GET THIS BOOK Blind Source Separation

This book provides readers a complete and self-contained set of knowledge about dependent source separation, including the latest development in this field. The book gives an overview on blind source separation where three promising blind separation techniques that can tackle mutually correlated sources are presented. The book further focuses on the non-negativity based methods, the time-frequency analysis based methods, and the pre-coding based methods, respectively.

Nonlinear Blind Source Separation and Blind Mixture Identification

Nonlinear Blind Source Separation and Blind Mixture Identification
  • Author : Yannick Deville,Leonardo Tomazeli Duarte,Shahram Hosseini
  • Publisher : Springer Nature
  • Release : 02 February 2021
GET THIS BOOK Nonlinear Blind Source Separation and Blind Mixture Identification

This book provides a detailed survey of the methods that were recently developed to handle advanced versions of the blind source separation problem, which involve several types of nonlinear mixtures. Another attractive feature of the book is that it is based on a coherent framework. More precisely, the authors first present a general procedure for developing blind source separation methods. Then, all reported methods are defined with respect to this procedure. This allows the reader not only to more easily

Springer Handbook of Speech Processing

Springer Handbook of Speech Processing
  • Author : Jacob Benesty,M. M. Sondhi,Yiteng Huang
  • Publisher : Springer Science & Business Media
  • Release : 28 November 2007
GET THIS BOOK Springer Handbook of Speech Processing

This handbook plays a fundamental role in sustainable progress in speech research and development. With an accessible format and with accompanying DVD-Rom, it targets three categories of readers: graduate students, professors and active researchers in academia, and engineers in industry who need to understand or implement some specific algorithms for their speech-related products. It is a superb source of application-oriented, authoritative and comprehensive information about these technologies, this work combines the established knowledge derived from research in such fast evolving

Latent Variable Analysis and Signal Separation

Latent Variable Analysis and Signal Separation
  • Author : Emmanuel Vincent,Arie Yeredor,Zbyněk Koldovský,Petr Tichavský
  • Publisher : Springer
  • Release : 14 August 2015
GET THIS BOOK Latent Variable Analysis and Signal Separation

This book constitutes the proceedings of the 12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICS 2015, held in Liberec, Czech Republic, in August 2015. The 61 revised full papers presented – 29 accepted as oral presentations and 32 accepted as poster presentations – were carefully reviewed and selected from numerous submissions. Five special topics are addressed: tensor-based methods for blind signal separation; deep neural networks for supervised speech separation/enhancement; joined analysis of multiple datasets, data fusion, and related topics; advances in nonlinear

Latent Variable Analysis and Signal Separation

Latent Variable Analysis and Signal Separation
  • Author : Petr Tichavský,Massoud Babaie-Zadeh,Olivier J.J. Michel,Nadège Thirion-Moreau
  • Publisher : Springer
  • Release : 13 February 2017
GET THIS BOOK Latent Variable Analysis and Signal Separation

This book constitutes the proceedings of the 13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017, held in Grenoble, France, in Feburary 2017. The 53 papers presented in this volume were carefully reviewed and selected from 60 submissions. They were organized in topical sections named: tensor approaches; from source positions to room properties: learning methods for audio scene geometry estimation; tensors and audio; audio signal processing; theoretical developments; physics and bio signal processing; latent variable analysis in observation sciences; ICA

Latent Variable Analysis and Signal Separation

Latent Variable Analysis and Signal Separation
  • Author : Yannick Deville,Sharon Gannot,Russell Mason,Mark D. Plumbley,Dominic Ward
  • Publisher : Springer
  • Release : 05 June 2018
GET THIS BOOK Latent Variable Analysis and Signal Separation

This book constitutes the proceedings of the 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018, held in Guildford, UK, in July 2018.The 52 full papers were carefully reviewed and selected from 62 initial submissions. As research topics the papers encompass a wide range of general mixtures of latent variables models but also theories and tools drawn from a great variety of disciplines such as structured tensor decompositions and applications; matrix and tensor factorizations; ICA methods; nonlinear mixtures; audio

Latent Variable Analysis and Signal Separation

Latent Variable Analysis and Signal Separation
  • Author : Fabian Theis,Andrzej Cichocki,Arie Yeredor,Michael Zibulevsky
  • Publisher : Springer Science & Business Media
  • Release : 01 March 2012
GET THIS BOOK Latent Variable Analysis and Signal Separation

This book constitutes the proceedings of the 10th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2012, held in Tel Aviv, Israel, in March 2012. The 20 revised full papers presented together with 42 revised poster papers, 1 keynote lecture, and 2 overview papers for the regular, as well as for the special session were carefully reviewed and selected from numerous submissions. Topics addressed are ranging from theoretical issues such as causality analysis and measures, through novel methods for employing the well-established concepts

Advances in Heuristic Signal Processing and Applications

Advances in Heuristic Signal Processing and Applications
  • Author : Amitava Chatterjee,Hadi Nobahari,Patrick Siarry
  • Publisher : Springer Science & Business Media
  • Release : 05 June 2013
GET THIS BOOK Advances in Heuristic Signal Processing and Applications

There have been significant developments in the design and application of algorithms for both one-dimensional signal processing and multidimensional signal processing, namely image and video processing, with the recent focus changing from a step-by-step procedure of designing the algorithm first and following up with in-depth analysis and performance improvement to instead applying heuristic-based methods to solve signal-processing problems. In this book the contributing authors demonstrate both general-purpose algorithms and those aimed at solving specialized application problems, with a special emphasis

On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling

On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
  • Author : Addisson Salazar
  • Publisher : Springer Science & Business Media
  • Release : 20 July 2012
GET THIS BOOK On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling

A natural evolution of statistical signal processing, in connection with the progressive increase in computational power, has been exploiting higher-order information. Thus, high-order spectral analysis and nonlinear adaptive filtering have received the attention of many researchers. One of the most successful techniques for non-linear processing of data with complex non-Gaussian distributions is the independent component analysis mixture modelling (ICAMM). This thesis defines a novel formalism for pattern recognition and classification based on ICAMM, which unifies a certain number of pattern

Source Separation and Machine Learning

Source Separation and Machine Learning
  • Author : Jen-Tzung Chien
  • Publisher : Academic Press
  • Release : 01 November 2018
GET THIS BOOK Source Separation and Machine Learning

Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the importance of machine learning perspectives. It illustrates how BSS problems are tackled through adaptive learning algorithms and model-based approaches using the latest information on mixture signals to build a BSS model that is seen as a statistical model for a whole system. Looking at different models, including independent component analysis (ICA), nonnegative matrix factorization (NMF), nonnegative tensor factorization (NTF), and