A new approach is proposed to describe the autowave processes responsible for plastic deformation localiza-tion in metals and alloys. The existence of a quasi-particle, which corresponds to a localized plastic flow au...A new approach is proposed to describe the autowave processes responsible for plastic deformation localiza-tion in metals and alloys. The existence of a quasi-particle, which corresponds to a localized plastic flow autowave, is postulated and its characteristics are determined. The above postulate leads to a number of cor-ollaries and quantitative assessments that are considered herein. The deformation processes occurring on the macro- and micro-scale levels are found to be directly related.展开更多
The discrete three-dimensional model of the adsorption-diffusion process was developed with three states using the comers of blocks within the framework of the theory of CA （cellular automata）. The construction of a...The discrete three-dimensional model of the adsorption-diffusion process was developed with three states using the comers of blocks within the framework of the theory of CA （cellular automata）. The construction of an asynchronous cellular automaton was used for the modeling, The implementation of the algorithm leads to a huge variety of dynamical regimes some of which are moving from the general chaos into a state of local and then global synchronization （within the framework of the model）.展开更多
This paper presents a coupled neural network, called output-threshold coupled neural network (OTCNN), which can mimic the autowaves in the present pulsed coupled neural networks (PCNNs), by the construction of mutual ...This paper presents a coupled neural network, called output-threshold coupled neural network (OTCNN), which can mimic the autowaves in the present pulsed coupled neural networks (PCNNs), by the construction of mutual coupling between neuron outputs and the threshold of a neuron. Based on its autowaves, this paper presents a method for finding the shortest path in shortest time with OTCNNs. The method presented here features much fewer neurons needed, simplicity of the structure of the neurons and the networks, and large scale of parallel computation. It is shown that OTCNN is very effective in finding the shortest paths from a single start node to multiple destination nodes for asymmetric weighted graph, with a number of iterations proportional only to the length of the shortest paths, but independent of the complexity of the graph and the total number of existing paths in the graph. Finally, examples for finding the shortest path are presented.展开更多
文摘A new approach is proposed to describe the autowave processes responsible for plastic deformation localiza-tion in metals and alloys. The existence of a quasi-particle, which corresponds to a localized plastic flow autowave, is postulated and its characteristics are determined. The above postulate leads to a number of cor-ollaries and quantitative assessments that are considered herein. The deformation processes occurring on the macro- and micro-scale levels are found to be directly related.
文摘The discrete three-dimensional model of the adsorption-diffusion process was developed with three states using the comers of blocks within the framework of the theory of CA （cellular automata）. The construction of an asynchronous cellular automaton was used for the modeling, The implementation of the algorithm leads to a huge variety of dynamical regimes some of which are moving from the general chaos into a state of local and then global synchronization （within the framework of the model）.
文摘This paper presents a coupled neural network, called output-threshold coupled neural network (OTCNN), which can mimic the autowaves in the present pulsed coupled neural networks (PCNNs), by the construction of mutual coupling between neuron outputs and the threshold of a neuron. Based on its autowaves, this paper presents a method for finding the shortest path in shortest time with OTCNNs. The method presented here features much fewer neurons needed, simplicity of the structure of the neurons and the networks, and large scale of parallel computation. It is shown that OTCNN is very effective in finding the shortest paths from a single start node to multiple destination nodes for asymmetric weighted graph, with a number of iterations proportional only to the length of the shortest paths, but independent of the complexity of the graph and the total number of existing paths in the graph. Finally, examples for finding the shortest path are presented.
