文档介绍：Adaptive Blind Signal and Image Processing Learning Algorithms and Applications Andrzej CICHOCKI Shun-ichi AMARI includes CD Contents Preface xxix 1 Introduction to Blind Signal Processing: Problems and Applications 1 Problem Formulations – An Overview 2 Generalized Blind Signal Processing Problem 2 Instantaneous Blind Source Separation and ponent Analysis 5 ponent Analysis for Noisy Data 11 Multichannel Blind Deconvolution and Separation 14 Blind Extraction of Signals 18 Generalized Multichannel Blind Deconvolution – State Space Models 19 Nonlinear State Space Models – Semi-Blind Signal Processing 21 Why State Space Demixing Models? 22 Potential Applications of Blind and Semi-Blind Signal Processing 23 Biomedical Signal Processing 24 Blind Separation of Electrocardiographic Signals of Fetus and Mother 25 Enhancement and position of EMG Signals 27 v vi CONTENTS EEG and Data MEG Processing 27 Application of ICA/BSS for Noise and Interference Cancellation in Multi-sensory Biomedical Signals 29 Cocktail Party Problem 34 munication Systems 35 Why Blind? 37 Image Restoration and Understanding 37 2 Solving a System of Algebraic Equations and Related Problems 43 Formulation of the Problem for Systems of Linear Equations 44 Least-Squares Problems 45 Basic Features of the Least-Squares Solution 45 Weighted Least-Squares and Best Linear Unbiased Estimation 47 work Structure-Least-Squares Criteria 49 Iterative Parallel Algorithms for Large and Sparse Systems 49 Iterative Algorithms with Non-negativity Constraints 51 Robust Circuit Structure by Using the Interactively Reweighted Least-Squares Criteria 54 Tikhonov Regularization and SVD 57 Least Absolute Deviation (1-norm) Solution of Systems of Linear Equations 61