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Cellular Neural Network (CNN) type analog parallel architectures have been studied both for their potential in high-speed image processing applications and for exhibiting rich and exciting nonlinear spatio-temporal dynamics among which waves and patterns. Such architectures have been also used as linear spatial filters for piecewise linear cells working in the linear central part of their characteristics...
Considerations concerning the dynamics of nonhomogeneous CNNpsilas are made and the possibility of using them for texture classifications is investigated by computer simulations.
Pattern formation in a new class of two-grid coupled CNN's characterized by the dependence of the array parameters on the voltage of one or several cells is investigated. The mechanism is similar to that used in harmonic oscillators to limit the oscillation amplitude. The effect of controlling each of the 6 parameters describing the linear central part of a piecewise linear CNN is analyzed and simulation...
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