Based on the standard self-organizing map neural network model and an integrate-and-fire mechanism, we introduce a kind of coupled map lattice system to investigate scale-invariance behavior in the activity of model n...Based on the standard self-organizing map neural network model and an integrate-and-fire mechanism, we introduce a kind of coupled map lattice system to investigate scale-invariance behavior in the activity of model neural populations. We let the parameter β, which together with α represents the interactive strength between neurons, have different function forms, and we find the function forms and their parameters are very important to our model''s avalanche dynamical behaviors, especially to the emergence of different avalanche behaviors in different areas of our system.展开更多
Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memor...Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memory and optimization. In this paper, we propose a novel covariance learning rule for multivalue patterns and apply it in memorization of gray scale images based on modified GCM model (S GCM). Analysis of retrieval results are given finally.展开更多
Application of the RTNN model for a system identification, prediction and control；Associative Memory Using Ratio Rule for Multi-valued Pattern Association；Batch-to-Batch Model-based Iterative Optimisation Control fo...Application of the RTNN model for a system identification, prediction and control；Associative Memory Using Ratio Rule for Multi-valued Pattern Association；Batch-to-Batch Model-based Iterative Optimisation Control for a Batch Polymerisation Reactor；Behavioural Plasticity in Autonomous Agents: A Comparison between Two Types of Controller；Channel Equalization Using Complex-Valued Recurrent Neural Networks；Classification of natural language sentences using neural networks；Combining a recurrent neural network and the output regulation theory for non-linear adaptive control。展开更多
To simulate the brain functions,a quantum associative memory combined with information preprocessing by a sparse coding model is presented. The sparse coding scheme is used to simulate the information transformation f...To simulate the brain functions,a quantum associative memory combined with information preprocessing by a sparse coding model is presented. The sparse coding scheme is used to simulate the information transformation from retina up to primary visual cortex (V1) along the visual path and the quantum associative memory is used to simulate the pattern processing functions of the brain such as the pattern storing,forgetting and retrieving. Experimental results show that the model exhibits good associative ability on face recognition. Considering the huge storage capacity,mass parallel-distributed processing ability and oscillatory phenomena of the quantum system,this model might be a biological plausible implementation.展开更多
文摘Based on the standard self-organizing map neural network model and an integrate-and-fire mechanism, we introduce a kind of coupled map lattice system to investigate scale-invariance behavior in the activity of model neural populations. We let the parameter β, which together with α represents the interactive strength between neurons, have different function forms, and we find the function forms and their parameters are very important to our model''s avalanche dynamical behaviors, especially to the emergence of different avalanche behaviors in different areas of our system.
文摘Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memory and optimization. In this paper, we propose a novel covariance learning rule for multivalue patterns and apply it in memorization of gray scale images based on modified GCM model (S GCM). Analysis of retrieval results are given finally.
文摘Application of the RTNN model for a system identification, prediction and control；Associative Memory Using Ratio Rule for Multi-valued Pattern Association；Batch-to-Batch Model-based Iterative Optimisation Control for a Batch Polymerisation Reactor；Behavioural Plasticity in Autonomous Agents: A Comparison between Two Types of Controller；Channel Equalization Using Complex-Valued Recurrent Neural Networks；Classification of natural language sentences using neural networks；Combining a recurrent neural network and the output regulation theory for non-linear adaptive control。
基金Natural Science Foundation of Fujian Province of China (No.2009J01306)
文摘To simulate the brain functions,a quantum associative memory combined with information preprocessing by a sparse coding model is presented. The sparse coding scheme is used to simulate the information transformation from retina up to primary visual cortex (V1) along the visual path and the quantum associative memory is used to simulate the pattern processing functions of the brain such as the pattern storing,forgetting and retrieving. Experimental results show that the model exhibits good associative ability on face recognition. Considering the huge storage capacity,mass parallel-distributed processing ability and oscillatory phenomena of the quantum system,this model might be a biological plausible implementation.
