Optimal solutions of selected cellular neural network applications by the hardware annealing method

An engineering annealing method for optimal solutions of cellular neural networks is presented. Cellular neural networks have great potential in solving many important scientific problems in signal processing and optimization by the use of predetermined templates. Hardware annealing (SaHyun Bang, 1994), which is a paralleled version of effective mean field annealing in analog networks, is a highly efficient method of finding optimal solutions for cellular neural networks. It does not require any stochastic procedure and henceforth can be very fast. The generalized energy function of the network is first increased by reducing the voltage gain of each neuron. Then, the hardware annealing searches for the globally minimum energy state by continuously increasing the gain of neurons. The process of global optimization by the proposed hardware annealing method can be described by eigenvalues in the time varying dynamic system.<
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