Deep neural networks : WASD neuronet models algorithms and applications Cover Half Title Series Page Title Page Copyright Page Dedication Contents Preface Authors Acknowledgments Part I: Single Input Single Output Neuronet 1. Single Input Euler Polynomial WASD Neuronet 1.1 Introduction 1.2 Neuronet Model and Theoretical Basis 1.3 WASD Algorithm 1.3.1 Weights direct determination 1.3.2 Structure automatic determination 1.4 Numerical Studies 1.5 Chapter Summary Appendix A: The 5th to 25th Euler Polynomials 2. Single Input Bernoulli Polynomial WASD Neuronet 2.1 Introduction 2.2 Neuronet Model and Theoretical Basis 2.3 WASD Algorithm 2.3.1 Weights direct determination 2.3.2 Structure automatic determination 2.4 Numerical Studies 2.5 Chapter Summary Appendix B: The 5th to 25th Bernoulli Polynomials 3. Single Input Laguerre Polynomial WASD Neuronet 3.1 Introduction 3.2 Neuronet Model and Theoretical Basis 3.3 WASD Algorithm 3.3.1 Weights direct determination 3.3.2 Structure automatic determination 3.4 Numerical Studies 3.5 Chapter Summary Part II: Two Input Single Output Neuronet 4. Two Input Legendre Polynomial WASD Neuronet 4.1 Introduction 4.2 Theoretical Basis 4.3 Neuronet Model and WASD Algorithms 4.3.1 Two input Legendre polynomial neuronet model 4.3.2 Two WASD algorithms 4.4 Numerical Studies 4.5 Chapter Summary 5. Two Input Chebyshev Polynomial of Class 1 WASD Neuronet 5.1 Introduction 5.2 Theoretical Basis 5.3 Neuronet Model and WASD Algorithm 5.3.1 Two input Chebyshev polynomial of Class 1 neuronet model 5.3.2 WASD algorithm 5.4 Numerical Studies 5.5 Chapter Summary 6. Two Input Chebyshev Polynomial of Class 2 WASD Neuronet 6.1 Introduction 6.2 Theoretical Basis 6.3 Neuronet Model and WASD Algorithm.