Cover13; -- Preface13; -- Contents13; -- Chapter 1 Introduction13; -- Logical Basis for Computation13; -- Logical Basis for Control13; -- Logical Basis of Communication13; -- Advanced Theory of Evolution13; -- Chapter 2 Multi/Infinite Dimensional Neural Networks, Multi/Infinite Dimensional Logic Theory13; -- 2.1 Introduction13; -- 2.2 Mathematical Model of Multidimensional Neural Networks13; -- 2.3 Convergence Theorem for Multidimensional Neural Networks13; -- 2.4 Multidimensional Logic Theory, Logic Synthesis13; -- 2.5 Infinite Dimensional Logic Theory: Infinite Dimensional Logic Synthesis13; -- 2.6 Neural Networks, Logic Theories, Constrained Static Optimization13; -- 2.7 Conclusions13; -- Chapter 3 Multi/Infinite Dimensional Coding Theory: Multi/Infinite Dimensional Neural Networks8212;Constrained Static Optimization13; -- 3.1 Introduction13; -- 3.2 Multidimensional Neural Networks: Minimum Cut computation in the Connection Structure -- 3.3 Multidimensional Error Correcting Codes: Associated Energy Functions8212;Generalized Neural Networks 13; -- 3.4 Multidimensional Error Correcting Codes: Relationship to Stable States of Energy Functions13; -- 3.5 Non-Binary Linear Codes13; -- 3.6 Non-Linear Codes13; -- 3.7 Constrained Static Optimization13; -- 3.8 Conclusions13; -- Chapter 4 Tensor State Space Representation: Multidimensional Systems13; -- 4.1 Introduction13; -- 4.2 State of the Art in Multi/Infinite Dimensional Static/Dynamic System Theory: Representation by Tensor Linear Operator13; -- 4.3 State Space Representation of Certain Multi/Infinite Dimensional Dynamical Systems: Tensor Linear Operator13; -- 4.4 Multi/Infinite Dimensional System Theory: Linear Dynamical Systems State Space Representation by Tensor Linear Operators13; -- 4.5 Stochastic Dynamical Systems13; -- 4.6 Distributed Dynamical Systems13; -- 4.7 Conclusions13; -- Chapter 5 Unified Theory of Control, Communication and Computation:Multidimensional Neural Networks13; -- 5.1 Introduction13; -- 5.2 One Dimensional Logic Functions, Codeword Vectors, Optimal Control Vectors: One Dimensional Neural Networks13; -- 5.3 Optimal Control Tensors: Multidimensional Neural Networks13; -- 5.4 Multidimensional Systems: Optimal Control Tensors, Codeword Tensors And Switching Function Tensors -- 5.5 Conclusions13; -- Chapter 6 Complex Valued Neural Associative Memory on the Complex Hypercube13; -- 6.1 Introduction13; -- 6.2 Features of the Proposed Model13; -- 6.3 Convergence Theorems13; -- 6.4 Conclusions13; -- Chapter 7 Optimal Binary Filters: Neural Networks13; -- 7.1 Introduction13; -- 7.2 Optimal Signal Design Problem: Solution13; -- 7.3 Optimal Filter Design Problem: Solution (Dual of Signal design Problem)13; -- 7.4 Conclusions13; -- Chapter 8 Linear Filter Model of a Synapse: Associated Novel Real/Complex Valued Neural Networks13; -- 8.1 Introduction13; -- 8.2 Continuous Time Perceptron and Generalizations13; -- 8.3 Abstract Mathematical Structure of Neuronal Models13; -- 8.4 Finite Impulse Response Model of Synapses: Neural Networks13; -- 8.5 Novel Continuous Time Associative Memory13; -- 8.6 Multidimensional Generalizations13; -- 8.7 Generalization to Complex Valued Neural Networks (CVNNs)13; -- 8.8. Conclusions13; -- Chapter 9 Novel Complex Valued Neural Networks13; -- 9.1 Introduction13; -- 9.2 Discrete Fourier Transform: Some Complex Valued Neural Networks.