Cover -- Preface -- Contents -- 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: Graphoid Codes -- 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 -- 9.3 Complex Valued Perceptron -- 9.4 Novel Model of a Neuron: Associated Neural Networks -- 9.5. Continuous Time Perceptron Learning Law -- 9.6 Some Important Generalizations -- 9.7 Some Open Questions -- 9.8 Conclusions -- Chapter 10 Advanced Theory of Evolution of Living Systems -- 10.1 Unified Theory: Cybernetics -- 10.2 Organic Evolution -- 10.3 Evolution of Living Systems: Innovative Principles -- 10.4 Conclusions -- Index.