All ITKnowledge
Source Code
Search Tips
Advanced Search
Title
Author
Publisher
ISBN
Please Select
-----------
Business & IT Mgmt
Certification & Training
Database & ERP
Desktop Apps
Graphic Design
General Internet
Hardware & OS
IBM RedBooks
Network & Telecom
Web & Software Dev
-----------
Public Archive
[an error occurred while processing this directive]
Preface
Acknowledgments
Chapter 1Introduction
1.1 General
1.2 Stochastical Aspects and Physics of Neural Activity
1.3 Neurocybernetic Concepts
1.4 Statistical Mechanics-Cybernetics-Neural Complex
1.5 Concluding Remarks
Chapter 2Neural and Brain Complex
2.1 Introduction
2.2 Gross Features of the Brain and the Nervous System
2.3 Neurons and Their Characteristics
2.4 Biochemical and Electrical Activities in Neurons
2.5 Mode(s) of Communication among Neurons
2.6 Collective Response of Neurons
2.7 Neural Net: A Self-Organizing Finite Automaton
2.8 Concluding Remarks
Chapter 3Concepts of Mathematical Neurobiology
3.1 Mathematical Neurobiology: Past and Present
3.2 Mathematics of Neural Activities
3.2.1 General considerations
3.2.2 Random sequence of neural potential spikes
3.2.3 Neural field theory
3.3 Models of Memory in Neural Networks
3.4 Net Function and Neuron Function
3.5 Concluding Remarks
Chapter 4Pseudo-Thermodynamics of Neural Activity
4.1 Introduction
4.2 Machine Representation of Neural Network
4.3 Neural Network
versus
Machine Concepts
4.3.1 Boltzmann Machine
4.3.2 McCulloch-Pitts Machine
4.3.3 Hopfield Machine
4.3.4 Gaussian Machine
4.4 Simulated Annealing and Energy Function
4.5 Cooling Schedules
4.6 Reverse-Cross and Cross Entropy Concepts
4.7 Activation Rule
4.8 Entropy at Equilibrium
4.9 Boltzmann Machine as a Connectionist Model
4.10 Pseudo-Thermodynamic Perspectives of Learning Process
4.11 Learning from Examples Generated by a Perceptron
4.12 Learning at Zero Temperature
4.13 Concluding Remarks
Chapter 5The Physics of Neural Activity: A Statistical Mechanics Perspective
5.1 Introduction
5.2 Cragg and Temperley Model
5.3 Concerns of Griffith
5.4 Littles Model
5.5 Thompson and Gibson Model
5.6 Hopfields Model
5.7 Perettos Model
5.8 Littles Model
versus
Hopfields Model
5.9 Ising Spin System
versus
Interacting Neurons
5.10 Liquid-Crystal Model
5.11 Free-Point Molecular Dipole Interactions
5.12 Stochastical Response of Neurons under Activation
5.13 Hamiltonian of Neural Spatial Long-Range Order
5.14 Spatial Persistence in the Nematic Phase
5.15 Langevin Machine
5.16 Langevin Machine
versus
Boltzmann Machine
5.17 Concluding Remarks
Chapter 6Stochastical Dynamics of the Neural Complex
6.1 Introduction
6.2 Stochastical Dynamics of the Neural Assembly
6.3 Correlation of Neuronal State Disturbances
6.4 Fokker-Planck Equation of Neural Dynamics
6.5 Stochastical Instability in Neural Networks
6.6 Stochastical Bounds and Estimates of Neuronal Activity
6.7 Stable States Search
via
Modified Bias Parameter
6.8 Noise-Induced Effects on Saturated Neural Population
6.9 Concluding Remarks
Chapter 7Neural Field Theory: Quasiparticle Dynamics and Wave Mechanics Analogies of Neural Networks
7.1 Introduction
7.2 Momentum-Flow Model of Neural Dynamics
7.3 Neural Particle Dynamics
7.4 Wave Mechanics Representation of Neural Activity
7.5 Characteristics of Neuronal Wave Function
7.6 Concepts of Wave Mechanics
versus
Neural Dynamics
7.7 Lattice Gas System Analogy of Neural Assembly
7.8 The Average Rate of Neuronal Transmission Flow
7.9 Models of Peretto and Little
versus
Neuronal Wave
7.10 Wave Functional Representation of Hopfields Network
7.11 Concluding Remarks
Chapter 8Informatic Aspects of Neurocybernetics
8.1 Introduction
8.2 Information-Theoretics of Neural Networks
8.3 Information Base of Neurocybernetics
8.4 Informatics of Neurocybernetic Processes
8.5 Disorganization in the Neural System
8.6 Entropy of Neurocybernetic Self-Regulation
8.7 Subjective Neural Disorganization
8.8 Continuous Neural Entropy
8.9 Differential Disorganization in the Neural Complex
8.10 Dynamic Characteristics of Neural Informatics
8.11 Jensen-Shannon Divergence Measure
8.12 Semiotic Framework of Neuroinformatics
8.13 Informational Flow in the Neural Control Process
8.14 Dynamic State of Neural Organization
8.15 Concluding Remarks
Bibliography
Appendix A
Appendix B
Appendix C
Index
Copyright ©
CRC Press LLC
Products
|
Contact Us
|
About Us
|
Privacy
|
Ad Info
|
Home
Use of this site is subject to certain
Terms & Conditions
,
Copyright © 1996-2000 EarthWeb Inc.
All rights reserved. Reproduction in whole or in part in any form or medium without express written
permission
of EarthWeb is prohibited. Read EarthWeb's
privacy
statement.