AbstractIn this paper, some new estimation results on the domain of attraction of memory patterns and exponential convergence rate of the network trajectories to memory patterns for Hopfield continuous associative memory are obtained. These results can be used for the evaluation of fault-tolerance capability and the synthesis procedures for Hopfield continuous feedback associative memory neural networks
AbstractIn this paper, some sufficient conditions for the local and global exponential stability of ...
A method for the storage of analog vectors, i.e., vectors whose components are real-valued, is devel...
Hopfield neural networks are a possible basis for modelling associative memory in living organisms. ...
AbstractIn this paper, the domain of attraction of memory patterns and the exponential convergence r...
Some results about estimation of the domain of attraction of memory patterns and exponential converg...
AbstractIn this paper, some new estimation results on the domain of attraction of memory patterns an...
This paper introduces the definition,principle,model and basic learning rules of feedback neural net...
Abstruct- Most of the neural network associative memory models deal with the storage of binary vecto...
This article is devoted to the issue of pattern recognition using neural network technologies. In pa...
Abstract We introduce a formal theoretical background, which includes theorems and their proofs, for...
A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying...
A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying...
This is a study of the dynamics of neural network as formulated by Hopfield in 1982. Various update ...
Attractor neural networks such as the Hopfield model can be used to model associative memory. An eff...
Nessa dissertação, é investigado o armazenamento e a recuperação de padrões de forma biologicamente...
AbstractIn this paper, some sufficient conditions for the local and global exponential stability of ...
A method for the storage of analog vectors, i.e., vectors whose components are real-valued, is devel...
Hopfield neural networks are a possible basis for modelling associative memory in living organisms. ...
AbstractIn this paper, the domain of attraction of memory patterns and the exponential convergence r...
Some results about estimation of the domain of attraction of memory patterns and exponential converg...
AbstractIn this paper, some new estimation results on the domain of attraction of memory patterns an...
This paper introduces the definition,principle,model and basic learning rules of feedback neural net...
Abstruct- Most of the neural network associative memory models deal with the storage of binary vecto...
This article is devoted to the issue of pattern recognition using neural network technologies. In pa...
Abstract We introduce a formal theoretical background, which includes theorems and their proofs, for...
A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying...
A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying...
This is a study of the dynamics of neural network as formulated by Hopfield in 1982. Various update ...
Attractor neural networks such as the Hopfield model can be used to model associative memory. An eff...
Nessa dissertação, é investigado o armazenamento e a recuperação de padrões de forma biologicamente...
AbstractIn this paper, some sufficient conditions for the local and global exponential stability of ...
A method for the storage of analog vectors, i.e., vectors whose components are real-valued, is devel...
Hopfield neural networks are a possible basis for modelling associative memory in living organisms. ...