Simulation and visualization of CNN dynamics

A new simulator for Cellular Neural Networks (CNNs) is presented. In contra st to other simulators, the CNN cells are visualized in a grid structure, t he values of input and states being represented by colors. Input and initia l images can easily be generated and changed even while the integration of the system is in progress, and an oscilloscope function allows the quantita tive study of CNN transients, thus providing insight into the dynamics of t he network. For those who are new to the world of CNNs, a series of predefined template s set and demonstrations are available, which makes the simulator a valuabl e educational tool. Advanced users and CNN expert can examine manually-ente red and parametrized templates and carry out experiments in a very broad sp ectrum of CNN theory and applications, including quantitative behavior, rob ustness aspects, settling time, state limitations, different output functio ns 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.