New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing Book

1	Introduction	1
I	Probabilistic neural networks in a non-stationary environment	7
2	Kernel functions for construction of probabilistic neural networks	9
3	Introduction to probabilistic neural networks	21
4	General learning procedure in a time-varying environment	59
5	Generalized regression neural networks in a time-varying environment	73
6	Probabilistic neural networks for pattern classification in a time-varying environment	135
II	Soft computing techniques for image compression	168
7	Vector quantization for image compression	169
8	The DPCM technique	179
9	The PVQ scheme	185
10	Design of the predictor	193
11	Design of the code-book	203
12	Design of the PVQ schemes	217
III	Recursive least squares methods for neural network learning and their systolic implementations	240
13	A family of the RLS learning algorithms	241
14	Systolic implementations of the RLS learning algorithms	283
	Appendix	329
	References	343