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Title: The Handbook of Brain Theory and Neural Networks: Second Edition by Michael A. Arbib ISBN: 0-262-01197-2 Publisher: Bradford Book Pub. Date: 15 November, 2002 Format: Hardcover Volumes: 1 List Price(USD): $195.00 |
Average Customer Rating: 5 (4 reviews)
Rating: 5
Summary: Basic science for consciousness
Comment: Research is tedious, but if you want to know the nitty-gritty of mind-brain theory and neural networking, this book is an invaluable resource for basic, relevant, and accessible papers on the subjects. Encompassing seminal works from an unusually broad range of disciplines, here is an outstanding reference for those concerned with the mechanisms of intelligence.
Rating: 5
Summary: Excellent compilation
Comment: This complilation of articles by leading experts in the field gives an excellent overview of studies in cognitive theory and the theory and applications of neural networks. The first two parts of the book give an overview and background of the properties of neurons and gives guidance to the reader on what sequence the articles are to be read. I did not read all of the articles, but only those that piqued my interest. I found the following articles particularly well-written and informative: 1. "Applications of Neural Networks": Outlines the diverse applications of neural networks to signal processing, time series, imaging, etc. 2. "Astronomy": Neural network applications in astronomy, such as adaptive optics and telescope guidance. 3. "Chains of Coupled Oscillators": Their connection with the lamprey central pattern generator. 4. "Chaos in Axons": An excellent review of chaos experimentally in squid axons and numerically with nerve equations. 5. "Collective Behavior of Coupled Oscillators": A study of the phase and complex Ginzburg-Landau model. 6. "Computer Modeling Methods for Neurons": Good overview of numerical modeling of neurons. 7. "Computing with Attractors": Overview of omputing and feedback networks with attractors and a fascinating discussion of the possible existence of attractors in the brain. 8. "Constrained Optimization and the Elastic Net": Useful discussion of application of neural networks to optimization problems. 9. "Data Clustering and Learning": Good discussion of parameter estimation of mixture models by parametric statistics and vector quantization of a data set by combinatorial optimization. 10. "Diffusion Models of Neuron Activity": Discusses 1-dimensional stochastic diffusion models for the neuron membrane potential. 11. "Disease: Neural Network Models": Interesting overview of neural net computational models of various mental illnesses. 12. "Dynamics and Bifurcation of Neural Networks": Discussion of neural nets and their behavior as dynamical systems. 13. "Emotion and Computational Neuroscience": Fascinating discussion of computational models of emotion. 14. "Investment Management": A discussion of tactical asset allocation neural network methods in asset management. 15. "Learning and Centralization: Theoretical Bounds": Overview of computational learning theory. 16. "Locust Flight": Interesting neural network study of the locust flight system. 17. "Neural Optimization": Discussion of combinatorial optimization using Ising and Potts neural networks. 18. "PAC Learning and Neural Networks": Overview of the Valiant "probabilistically correct learning paradigm in neural networks. 19. "Protein Structure Prediction": Neural network applications to prediction of protein secondary structure. 20. "Schema Theory": Extremely interesting overview of schemas. 21. "Speech Recognition: Pattern Matching": Excellent discussion of the applications of hidden Markov models to speech recognition. 22. "Statistical Mechanics of Neural Networks": Discussion of the use of the Hopfield model in neural networks. 23. Vapnik-Chervonenkis Dimension of Neural Networks": Very interesting discussion of the VC-dimension of neural networks.
Rating: 5
Summary: Neural Network Bible
Comment: This is THE neural network and brain theory reference. Owning it is like owning an entire library, though much more compact.
If you take a look at the table of contents, you'll see the massive value in this book. If you're into neural nets and brain theory, or want to be, you need this book.
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Title: Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems by Peter Dayan, L. F. Abbott ISBN: 0262041995 Publisher: MIT Press Pub. Date: 01 December, 2001 List Price(USD): $50.00 |
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Title: Spikes: Exploring the Neural Code (Computational Neuroscience) by Fred Rieke, David Warland ISBN: 0262681080 Publisher: Bradford Book Pub. Date: 25 June, 1999 List Price(USD): $30.00 |
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Title: Biophysics of Computation: Information Processing in Single Neurons (Computational Neuroscience) by Christof Koch ISBN: 0195104919 Publisher: Oxford University Press Pub. Date: 01 November, 1998 List Price(USD): $79.95 |
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Title: Principles of Neural Science by Eric R. Kandel, James H. Schwartz, Thomas M. Jessell ISBN: 0838577016 Publisher: McGraw-Hill/Appleton & Lange Pub. Date: 05 January, 2000 List Price(USD): $95.00 |
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Title: Neural Engineering: Computation, Representation, and Dynamics in Neurobiological Systems by Chris Eliasmith, C. H. Anderson ISBN: 0262050714 Publisher: Bradford Book Pub. Date: 01 December, 2002 List Price(USD): $49.95 |
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