Bøger af Yunong Zhang

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 led 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.

It also uses simulations to substantiate their efficacy and show the feasibility of the presented ZD approach (i.e., different ZFs leading to different ZD models), which is further applied to the repetitive motion planning (RMP) of redundant robots, showing its application potential.

This book offers the latest in the parallel solution of integral equations for both in-core and out-of-core modes. User-friendly computer code is provided, with a strong and unique capability for solving challenging electromagnetic field problems consisting of complex material structures.

The real-time solution to a mathematical problem arises in numerous fields of science, engineering, and business. This book presents ZNN, ZD or ZND theory that formalises these problems and solutions in the time-varying context, and provides compact models that could solve those dynamic problems.

This book presents four typical motion planning schemes based on optimization techniques, including the fundamental RMP scheme and its extensions. These schemes are unified as quadratic programs, which are solved by neural networks or numerical algorithms.