Neural network learning and expert systems  
Stephen I. Gallant
MIT Press
Most neural network programs for personal computers simply control a set                  of fixed, canned network-layer algorithms with pulldown menus. This new tutorial                  offers hands-on neural network experiments with a different approach. A simple                  matrix language lets users create their own neural networks and combine networks,                  and this is the only currently available software permitting combined simulation of                  neural networks together with other dynamic systems such as robots or physiological                  models. The enclosed student version of DESIRE/NEUNET differs from the full system                  only in the size of its data area and includes a screen editor, compiler, color                  graphics, help screens, and ready-to-run examples. Users can also add their own help                  screens and interactive menus.The book provides an introduction to neural networks                  and simulation, a tutorial on the software, and many complete programs including                  several backpropagation schemes, creeping random search, competitive learning with                  and without adaptive-resonance function and "conscience," counterpropagation,                  nonlinear Grossberg-type neurons, Hopfield-type and bidirectional associative                  memories, predictors, function learning, biological clocks, system identification,                  and more.In addition, the book introduces a simple, integrated environment for                  programming, displays, and report preparation. Even differential equations are                  entered in ordinary mathematical notation. Users need not learn C or LISP to program                  nonlinear neuron models. To permit truly interactive experiments, the extra-fast                  compilation is unnoticeable, and simulations execute faster than PC FORTRAN.The                  nearly 90 illustrations include block diagrams, computer programs, and                  simulation-output graphs.Granino A. Kom has been a Professor of Electrical                  Engineering at the University of Arizona and has worked in the aerospace industry                  for a decade. He is the author of ten other engineering texts and                  handbooks.