BIOMIMETIC PATTERN RECOGNITION & MULTI-WEIGHT NEURON mainly written by Academician Wang Shoujue is planning to be published by World Scientific in Singapore in 2009.

    The book illuminates the high dimensional geometry analysis of Biomimetic Pattern Recognition (BPR) and its applications. One important theoretically basis out of BPR is the Principle of Homology Continuity (PHC), which offers one solid foundation for BPR's performing "cognition" instead of "distinction" or "classification" to sample sets.

    On another part, the Multi-Weight Neuron (MWN) which operates relations between many weight vectors and one input vector in one neuron and is more suitable for BPR, is further introduced. The special trait of MWN structure not only makes it significant and convenient to deal with tough nonlinear feature space, but also takes routine neuron functions into account. For a better understanding, several BPR applications with experimental results are given in detail, and BPR抯 advantages over MWN networks on covering distributed sample sets for cognition are explained.

Contents:

• Review of Statistical Pattern Recognition:
• Introduction
• Kernel of Statistical Pattern Recognition and Preprocessing
• Support Vector Machine
• Biomimetic Pattern Recognitions:
• Introduction
• High Dimensional Biomimetic Informatics
• Concepts of Biomimetic Pattern Recognitions
• Features of Biomimetic Pattern Recognitions
• Some Applications
• Multi-Weight Neuron:
• Introduction
• Nature of Multi-Weight Neuron
• Relation Between Multi-Weight Neuron and Biomimetic Pattern Recognition
• Some Applications