New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing - Leszek Rutkowski

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Sommaire:
1 Introduction.- I Probabilistic Neural Networks in a Non-stationary Environment.- 2 Kernel Functions for Construction of Probabilistic Neural Networks.- 3 Introduction to Probabilistic Neural Networks.- 4 General Learning Procedure in a Time-Varying Environment.- 5 Generalized Regression Neural Networks in a Time-Varying Environment.- 6 Probabilistic Neural Networks for Pattern Classification in a Time-Varying Environment.- II Soft Computing Techniques for Image Compression.- 7 Vector Quantization for Image Compression.- 8 The DPCM Technique.- 9 The PVQ Scheme.- 10 Design of the Predictor.- 11 Design of the Code-book.- 12 Design of the PVQ Schemes.- III Recursive Least Squares Methods for Neural Network Learning and their Systolic Implementations.- 13 A Family of the RLS Learning Algorithms.- 14 Systolic Implementations of the RLS Learning Algorithms.- References.