Pattern Recognition Using Asymmetric Neural Networks

This thesis is composed of two parts. In the first one, we have studied the dynamical behaviors of the asymmetric neural networks designed by t he Monte Carlo Adaptation rule, and their great potential for pattern reco gnition is mainly emphasized. The second one shows a primary investigat ion for the spatial shift of the solitons in nonlinear lattices.The Monte Carlo Adaptation (MC-adaptation) rule is proposed by Pro f. Hong Zhao to design asymmetric neural networks with associative me mory. The basic idea of this global study rule is to obtain a certain optimi zation by adaptively changing the values of the connection matrix. By ap plying this rule, one may find three different dynamical phases, i.e. the ch aos phase, the memory phase and the mixture phase, which are essentially important not only for practical applications but also for understanding th e global dynamical behaviors of the general discrete systems.Therefore, this thesis is start with a brief introduction of the Monte Ca rlo Adaptation rule. And then, we give the basic ideas of using the neural networks with chaos phase for pattern recognition. Their intrinsic advanta ges for this purpose are emphasized. To make them more utility and contr ollability, we have modified the original MC-adaptation rule. As an exam ple, this modified rule has been applied for the printed Chinese Character recognition. Based on the analysis of the distribution of the local fields obtained by the memory patterns, we have further extended the MC-adaptati on rule to be suitable for designing the multi-states neural networks.Finally, we quantitatively measure the spatial shifts of the solitons usi ng the method of molecular dynamics. Although it is commonly believed that the solitons will make a random spatial shift when it interacts with an other quasiparticle, the corresponding "signature" has never been observe d neither experimentally or in a numerical simulation. For the first time, we give a direct evidence of this phenomenon and make a qualitative anal ysis for its mechanism.