Neural Networks Theory

1. Introduction

Part I. The Structure of Neural Networks

2. Transfer from the Logical Basis of Boolean Elements “AND, OR, NOT” to the Threshold Logical Basis

3. Qualitative Characteristics of Neural Network Architectures

4. Optimization of Cross Connection Multilayer Neural Network Structure

5. Continual Neural Networks

Part II. Optimal Models of Neural Networks

6. Investigation of Neural Network Input Signal Characteristics

7. Design of Neural Network Optimal Models

8. Analysis of the Open-Loop Neural Networks

9. Development of Multivariable Function Extremum Search Algorithms

Part III. Adaptive Neural Networks

10. Neural Network Adjustment Algorithms

11. Adjustment of Continuum Neural Networks

12. Selection of Initial Conditions During Neural Network Adjustment — Typical Neural Network Input Signals

13. Analysis of Closed-Loop Multilayer Neural Networks

14. Synthesis of Multilayer Neural Networks with Flexible Structure

15. Informative Feature Selection in Multilayer Neural Networks

Part IV. Neural Network Reliability and Diagnostics

16. Neural Network Reliability

17. Neural Network Diagnostics

18. Methods of Problem Solving in the Neural Network Logical Basis

DRM-restrictions

Printing: not available
Clipboard copying: not available

Nyckelord: TECHNOLOGY & ENGINEERING / General TEC000000