Multidimensional neural networks : unified theory /

About the Book: The book ''Multidimensional Neural Networks (MDNNs): Unified Theory'' has been conceived for serving 3 types of users: Senior undergraduate/graduate students, practising engineers, and advanced neural network researchers. This book is based on the following innova...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Murthy, G. Rama
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New Delhi : New Age International, ©2008.
Temas:
Neural networks (Computer science)
Réseaux neuronaux (Informatique)
COMPUTERS > Neural Networks.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Chapter 1. Introduction
  • Logical Basis for Computation
  • Logical Basis for Control
  • Logical Basis of Communication
  • Advanced Theory of Evolution
  • Chapter 2. Multi/Infinite Dimensional Neural Networks, Multi/Infinite Dimensional Logic Theory
  • 2.1 Introduction
  • 2.2 Mathematical Model of Multidimensional Neural Networks
  • 2.3 Convergence Theorem for Multidimensional Neural Networks
  • 2.4 Multidimensional Logic Theory, Logic Synthesis
  • 2.5 Infinite Dimensional Logic Theory : Infinite Dimensional Logic Synthesis
  • 2.6 Neural Networks, Logic Theories, Constrained Static Optimization
  • 2.7 Conclusions
  • Chapter 3. Multi/Infinite Dimensional Coding Theory : Multi/Infinite Dimensional Neural Networks, Constrained Static Optimization
  • 3.1 Introduction
  • 3.2 Multidimensional Neural Networks : Minimum Cut computation in the Connection Structure
  • 3.3 Multidimensional Error Correcting Codes : Associated Energy Functions, Generalized Neural Networks
  • 3.4 Multidimensional Error Correcting Codes: Relationship to Stable States of Energy Functions
  • 3.5 Non-Binary Linear Codes
  • 3.6 Non-Linear Codes
  • 3.7 Constrained Static Optimization
  • 3.8 Conclusions
  • Chapter 4. Tensor State Space Representation: Multidimensional Systems
  • 4.1 Introduction
  • 4.2 State of the Art in Multi/Infinite Dimensional Static/Dynamic System Theory : Representation by Tensor Linear Operator
  • 4.3 State Space Representation of Certain Multi/Infinite Dimensional Dynamical Systems : Tensor Linear Operator
  • 4.4 Multi/Infinite Dimensional System Theory : Linear Dynamical Systems State Space Representation by Tensor Linear Operators
  • 4.5 Stochastic Dynamical Systems
  • 4.6 Distributed Dynamical Systems
  • 4.7 Conclusions
  • Chapter 5. Unified Theory of Control, Communication and Computation : Multidimensional Neural Networks
  • 5.1 Introduction
  • 5.2 One-Dimensional Logic Functions, Codeword Vectors, Optimal Control Vectors : One-Dimensional Neural Networks
  • 5.3 Optimal Control Tensors : Multidimensional Neural Networks
  • 5.4 Multidimensional Systems : Optimal Control Tensors, Codeword Tensors And Switching Function Tensors
  • 5.5 Conclusions
  • Chapter 6. Complex Valued Neural Associative Memory on the Complex Hypercube
  • 6.1 Introduction
  • 6.2 Features of the Proposed Model
  • 6.3 Convergence Theorems
  • 6.4 Conclusions
  • Chapter 7. Optimal Binary Filters : Neural Networks
  • 7.1 Introduction
  • 7.2 Optimal Signal Design Problem : Solution
  • 7.3 Optimal Filter Design Problem : Solution (Dual of Signal design Problem)
  • 7.4 Conclusions
  • Chapter 8. Linear Filter Model of a Synapse : Associated Novel Real/Complex Valued Neural Networks
  • 8.1 Introduction
  • 8.2 Continuous Time Perceptron and Generalizations
  • 8.3 Abstract Mathematical Structure of Neuronal Models
  • 8.4 Finite Impulse Response Model of Synapses : Neural Networks
  • 8.5 Novel Continuous Time Associative Memory
  • 8.6 Multidimensional Generalizations
  • 8.7 Generalization to Complex Valued Neural Networks (CVNNs)
  • 8.8. Conclusions
  • Chapter 9. Novel Complex Valued Neural Networks
  • 9.1 Introduction
  • 9.2 Discrete Fourier Transform : Some Complex Valued Neural Networks
  • Chapter 10. Advanced Theory of Evolution of Living Systems.

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