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Independent Component Analysis and Signal Separation

Independent Component Analysis and Signal Separation

Detail Book : Independent Component Analysis and Signal Separation written by Mike E. Davies, published by Springer Science & Business Media which was released on 28 August 2007. Download Independent Component Analysis and Signal Separation Books now! Available in PDF, ePub and Kindle. This book constitutes the refereed proceedings of the 7th International Conference on Independent Component Analysis and Blind Source Separation, ICA 2007, held in London, UK, in September 2007. It covers algorithms and architectures, applications, medical applications, speech and signal processing, theory, and visual and sensory processing.

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Author : Mike E. Davies
Release Date : 28 August 2007
Publisher : Springer Science & Business Media
Rating : 4/5 (from 21 users)
Pages : 847
ISBN : 3540744932
Format : PDF, ePUB, KF8, PDB, MOBI, Tuebl
Independent Component Analysis and Signal Separation

Independent Component Analysis and Signal Separation

This book constitutes the refereed proceedings of the 7th International Conference on Independent Component Analysis and Blind Source Separation, ICA 2007, held in London, UK, in September 2007. It covers algorithms and architectures, applications, medical applications, speech and signal processing, theory, and visual and sensory processing.

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Independent Component Analysis

Independent Component Analysis

A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons of computational and conceptual simplicity, the representation is often sought as a linear transformation of the original data. In other words, each

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Independent Component Analysis and Signal Separation

Independent Component Analysis and Signal Separation

This volume contains the papers presented at the 8th International Conf- ence on Independent Component Analysis (ICA) and Source Separation held in Paraty, Brazil, March 15–18, 2009. This year's event resulted from scienti?c collaborations between a team of researchers from ?ve di?erent Brazilian u- versities and received the support of

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Blind Source Separation

Blind Source Separation

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

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Handbook of Blind Source Separation

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

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Adaptive Blind Signal and Image Processing

Adaptive Blind Signal and Image Processing

With solid theoretical foundations and numerous potential applications, Blind Signal Processing (BSP) is one of the hottest emerging areas in Signal Processing. This volume unifies and extends the theories of adaptive blind signal and image processing and provides practical and efficient algorithms for blind source separation: Independent, Principal, Minor Component

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Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy

Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy

This book constitutes the refereed joint proceedings of the 4th International Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019.

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Blind Source Separation

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

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Biomedical Image Analysis and Mining Techniques for Improved Health Outcomes

Biomedical Image Analysis and Mining Techniques for Improved Health Outcomes

Every second, users produce large amounts of image data from medical and satellite imaging systems. Image mining techniques that are capable of extracting useful information from image data are becoming increasingly useful, especially in medicine and the health sciences. Biomedical Image Analysis and Mining Techniques for Improved Health Outcomes addresses

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Blind Source Separation

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

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Unsupervised Signal Processing

Unsupervised Signal Processing

Unsupervised Signal Processing: Channel Equalization and Source Separation provides a unified, systematic, and synthetic presentation of the theory of unsupervised signal processing. Always maintaining the focus on a signal processing-oriented approach, this book describes how the subject has evolved and assumed a wider scope that covers several topics, from well-established

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Neural Networks and Statistical Learning

Neural Networks and Statistical Learning

Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop

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Parallel and Distributed Computing  Applications and Technologies

Parallel and Distributed Computing Applications and Technologies

This book constitutes the refereed proceedings of the 5th International Conference on Parallel and Distributed Computing, Applications and Technologies; PDCAT 2004, held in Singapore in December 2004. The 173 papers presented were carefully reviewed and selected from 242 submissions. The papers focus on parallel and distributed computing from the perspectives of algorithms, networking and

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Advances in Neural Information Processing Systems 12

Advances in Neural Information Processing Systems 12

The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented

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Modern Multivariate Statistical Techniques

Modern Multivariate Statistical Techniques

This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.

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