Zhang Time Discretization (ZTD) Formulas and Applications
-
GET 10% OFF
- Publisher's listprice GBP 54.99
-
24 827 Ft (23 645 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 10% (cc. 2 482 Ft off)
- Discounted price 22 345 Ft (21 281 Ft + 5% VAT)
22 345 Ft
Availability
printed on demand
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number 1
- Publisher CRC Press
- Date of Publication 21 June 2026
- ISBN 9781032807355
- Binding Paperback
- No. of pages323 pages
- Size 254x178 mm
- Weight 660 g
- Language English
- Illustrations 218 Illustrations, black & white 697
Categories
Short description:
The 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.
MoreLong description:
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.
MoreTable of Contents:
1 Future Matrix Right Pseudoinversion 2 Future Equality-Constrained Quadratic Programming 3 Future Matrix Inversion With Noises 4 Future Matrix Pseudoinversion 5 Future Constrained Nonlinear Optimization With O(g3) 6 Future Unconstrained Nonlinear Optimization With O(g4) 7 Future Different-Layer Inequation-Equation System Solving With O(g5) 8 Future Matrix Square Root Finding With O(g6) 9 Tracking Control of Serial and Parallel Manipulators 10 Future Matrix Inversion with Sometimes-Singular Coefficient Matrix 11 Repetitive Motion Control of Redundant Manipulators 12 Future Different-Layer Equation System Solving 13 Future Matrix Equations Solving 14 Minimum Joint Motion Control of Redundant Manipulators 15 Euler-Precision General Formula of ZTD 16 Lagrange Numerical-Differentiation Formulas
More
