Non-Linear Feedback Neural Networks
This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved solutions are needed. The non-linear synapse neural network (NoSyNN) is one such possibility and is discussed in detail in this book. This book also discusses the applications in computationally intensive tasks like graph coloring, ranking, and linear as well as quadratic programming. The material in the book is useful to students, researchers and academician working in the area of analog computation.
First dedicated book on non-linear feedback neural networksContains thorough discussion on transcendental energy functionIncludes special chapter on Hopfield Network, its applications, and limitationsCadence OrCAD circuit files for all the circuit simulations discussed in the bookUseful material for researchers working in the area of analog computation