- 355 pages
- English
- ePUB (mobile friendly)
- Only available on web
Zhang Time Discretization (ZTD) Formulas and Applications
About This Book
This book aims to solve the discrete implementation problems of continuous-time neural network models while improving the performance of neural networks by using various Zhang Time Discretization (ZTD) formulas.
The authors summarize and present the systematic derivations and complete research of ZTD formulas from special 3S-ZTD formulas to general NS-ZTD formulas. These finally lead to their proposed discrete-time Zhang neural network (DTZNN) algorithms, which are more efficient, accurate, and elegant. This book will open the door to scientific and engineering applications of ZTD formulas and neural networks, and will be a major inspiration for studies in neural network modeling, numerical algorithm design, prediction, and robot manipulator control.
The book will benefit engineers, senior undergraduates, graduate students, and researchers in the fields of neural networks, computer mathematics, computer science, artificial intelligence, numerical algorithms, optimization, robotics, and simulation modeling.
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Table of contents
- Cover Page
- Half-Title Page
- Title Page
- Copyright Page
- Dedication Page
- Contents
- Figures
- Tables
- Preface
- Acknowledgments
- Part I Zhang-Taylor Discretization Formula and Applications
- Part II ZTD 6321 Formula and Applications
- Part III General Formulas and Applications of ZTD
- Part IV O(g3) ZTD Formulas and Applications
- Part VO(g4) ZTD Formulas and Applications
- Part VI O(g5) ZTD Formulas and Applications
- Part VII Miscellaneous
- Bibliography
- Glossary
- Index