Computational techniques for the analysis and design of structural dynamic systems using numerical methods have been the focus of an enormous amount of research for several decades. In general, the numerical methods utilized to solve these problems include two phases: (a) spatial discretization by either the finite element method (FEM) or the finite difference method (FDM), and (b) solution of systems of time dependent second-order ordinary differential equations. In addition, the significantly powerful advances in computer systems capabilities have put on the desks of structural systems designers enormous computing power either by means of increasingly effective computer workstations or else through PCs (personal computers), whose increasing power has succeeded in marginalizing the computational power differences between PCs and workstations in many cases. This volume is a comprehensive treatment of the issues involved in computational techniques in structural dynamic systems.

From the Back Cover:

Inspired by the structure of the human brain, artificial neural networks have found many applications due to their ability to solve cumbersome or intractable problems by learning from data. Neural networks can adapt to new environments by learning, and deal with information that is noisy. inconsistent, vague, or probabilistic. This volume of Neural Network Systems Techniques and Applications is devoted to Optimization Techniques, including systems structures and computional methods.

Coverage includes:

A unified view of optimal learning
Orthogonal transformation techniques
Sequential constructiive techniques
Fast back propagation algorithms
Neural networks with nonstationary or dynamic outputs
Applications to constraint satisfaction
Unsupervised learning neural networks
Optimum Cerebellar Model of Articulation Controller systems
A new statistical theory of optimum neural learning
The role of the Radial Basis Function in nonlinear dynamical systems

Practitioners, researchers, and students in industrial, manufacturing, mechanical, electrical, and computer engineering will find this volume a unique reference to a diverse array of methods for achieving optimization.

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