Simulated annealing and morphology neural networks
Jennifer L. Davidson · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
Artificial neural networks have proven to be quite useful for a variety of different applications. A recent addition to the arena of neural networks, morphology neural networks use a morphology-like operation as their basic nodal calculation, instead of the usual linear operation. Several morphology neural nets have been developed, and lattice-type learning rules have been used to train these networks. In this paper, we present a different kind of learning rule for morphology neural nets that is based on the simulated annealing algorithm. Simulated annealing has been applied to many different areas involving optimization.