Buch, Englisch, 256 Seiten, Format (B × H): 164 mm x 240 mm, Gewicht: 476 g
Buch, Englisch, 256 Seiten, Format (B × H): 164 mm x 240 mm, Gewicht: 476 g
ISBN: 978-0-8058-1337-1
Verlag: Taylor & Francis Inc
This book introduces a new neural network model called CALM, for categorization and learning in neural networks. The author demonstrates how this model can learn the word superiority effect for letter recognition, and discusses a series of studies that simulate experiments in implicit and explicit memory, involving normal and amnesic patients. Pathological, but psychologically accurate, behavior is produced by "lesioning" the arousal system of these models. A concise introduction to genetic algorithms, a new computing method based on the biological metaphor of evolution, and a demonstration on how these algorithms can design network architectures with superior performance are included in this volume.
The role of modularity in parallel hardware and software implementations is considered, including transputer networks and a dedicated 400-processor neurocomputer built by the developers of CALM in cooperation with Delft Technical University. Concluding with an evaluation of the psychological and biological plausibility of CALM models, the book offers a general discussion of catastrophic interference, generalization, and representational capacity of modular neural networks. Researchers in cognitive science, neuroscience, computer simulation sciences, parallel computer architectures, and pattern recognition will be interested in this volume, as well as anyone engaged in the study of neural networks, neurocomputers, and neurosimulators.
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Contents: Part I: CALM: Categorizing and Learning Module. Introduction. Description of CALM. Simulation Studies of Performance and Self-Organization in CALM. Part II: Application. Psychological Models. Pattern Recognition as a Practical Application. Genetic Algorithms: Modularity, Learning, and Network Design. Part III: Revisiting Modularity. Evaluation of CALM. Appendices: Hardware and Software for Neural Networks. Virtual Implementations on Transputer Networks. Hybrid Implementation: the BSP400, a Dedicated Multiprocessor. Physical Implementation: Some Notes on CALM in Analog Hardware. Modular Neurosimulators.
