Associative neural memories--a class of artificial neural networks--are among the most extensively studied and best understood neural paradigms. This volume brings together pioneering work on associative neural memory and hardware implementation by leading international researchers. The first part describes associative neural models that have close connections to biological or psychological aspects of memory, and demonstrates the important contributions that neurobiology can make to the design of artificial neural networks. Subsequent parts of the book present more complex extensions of the simple memory models, studying their recall capabilities, analyzing various characteristics-- such as capacity, convergence dynamics, and fault tolerance--and describing the hardware implementation of such memories. This book will be of interest to computer science professionals and students as well as to cognitive scientists interested in neural networks.