Publisher's Synopsis
Providing a comprehensive introduction to the use of neural networks in mechanical engineering applications, this book begins with an overview of different neural network topologies in the first two parts. Functioning of the human brain is explained as an analogy with artificial models. Unsupervised models like Hopfield, Bi-directional Associative Memory, fuzzy Associative Memory, Adaptive Resonance Theory, kohonen, as well as supervised architectures like Multi-Layer Perceptron, Counter Propagation networks and Radial Basis Function Networks are presented in detail with numerical examples.
The third part deals with applications of artificial neural networks for solving of design optimization problems, forward and inverse dynamic analysis applications and system identification and monitoring, as well as motion and vibration control in robotics and structural engineering. Software implementations for neural networks in C/C++ language and necessary optimization techniques in network training are given in Appendices.
