Analog cellular networks for multisensor fusion and control

Analog modular architectures, derived from the computational paradigm of st ate-controlled cellular neural networks (SC-CNNs), are considered in this b rief to process signals gathered from a distributed set of sensors. A novel design methodology for choosing the "local" system parameters so as to obt ain the desired "global" signal processing function is proposed together wi th some theoretical results on sufficient conditions that guarantee asympto tic stability. An experimental prototype of cellular neural network for mul tisensor data fusion and control applications is presented and its adoption in the field of smart structures is discussed.