SIMULATION AND VISUALIZATION OF CNN DYNAMICS

Abstract

A new simulator for Cellular Neural Networks (CNNs) is presented. In contrast to other simulators, the CNN cells are visualized in a grid structure, the values of input and states being represented by colors. Input and initial images can easily be generated and changed even while the integration of the system is in progress, and an oscilloscope function allows the quantitative study of CNN transients, thus providing insight into the dynamics of the network. For those who are new to the world of CNNs, a series of predefined templates set and demonstrations are available, which makes the simulator a valuable educational tool. Advanced users and CNN expert can examine manually-entered and parametrized templates and carry out experiments in a very broad spectrum of CNN theory and applications, including quantitative behavior, robustness aspects, settling time, state limitations, different output functions and numerical integration methods. The simulator is written in Java and publicly available on WWW and will run on any Web browser of the newer generations.