Cellular Nonlinear/neural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm. Analogic cellular computers based on CNNs are
set to change the way analog signals are processed and are paving the way to an entire new analog computing industry.

This unique undergraduate-level textbook includes many examples and exercises, including CNN simulator and development software accessible via the Internet. It is an ideal introduction to CNNs
and analogic cellular computing for students, researchers, and engineers from a wide range of disciplines. Although its prime focus is on visual computing, the concepts and techniques described
in the book will be of great interest to those working in other areas of research, including modeling of biological, chemical, and physical processes.

Leon Chua is a Professor of Electrical Engineering and Computer Science at the University of California, Berkeley where he coinvented the CNN in 1988 and holds several patents related to CNN
Technology. He received the Neural Network Pioneer Award, 2000.

Tamas Roska is a Professor of Information Technology at the P ́ zm ́ ny P. Catholic University of Budapest and head of the Analogical and Neural Computing Laboratory of the Computer and Automation Research Institute of the Hungarian Academy of Sciences, Budapest and was an early pioneer of CNN technology and a coinventor of the CNN Universal Machine as an analogic supercomputer, He has also spent 12 years as a part-time visiting scholar at the University of
California at Berkeley.