Numerical simulations of a single layer recurrent neural network model in which the synaptic connection matrix is formed by summing cyclic products of succesive patterns show that complex dynamics can occur with the reduction of a connectivity parameter which is the number of connection between neurons. The structure in these dynamics is discussed from the viewpoint of realizing complex function using complex dynamics
AbstractIt is proposed that chaotic attractors incorporated in neural net models can represent class...
The remarkable properties of information-processing by biological and artificial neuronal networks a...
Associative memory dynamics in neural networks are generally based on attractors. Retrieval based on...
Numerical simulations of a single layer recurrent neural network model in which the synaptic connect...
The neural net computer simulations which will be presented here are based on the acceptance of a se...
At a first glance, artificial neural networks, with engineered learning algorithms and carefully cho...
Most theoretical studies of the computational capabilities of balanced, recurrent E/I networks assu...
One way to understand the brain is in terms of the computations it performs that allow an organism t...
We study a family of discrete-time recurrent neural network models in which the synaptic connectivit...
Chaos in dynamical systems potentially provides many different dynamical states arising from a singl...
tructure of a strange attractor in the phase space without getting stuck at local minima. This abili...
Attractor properties of a popular discrete-time neural network model are illustrated through numeric...
Abstract. It has been proposed that chaos can serve as a reservoir providing an infinite number of d...
Self-organization is thought to play an important role in structuring nervous systems. It frequently...
Self-organization is thought to play an important role in structuring nervous systems. It frequently...
AbstractIt is proposed that chaotic attractors incorporated in neural net models can represent class...
The remarkable properties of information-processing by biological and artificial neuronal networks a...
Associative memory dynamics in neural networks are generally based on attractors. Retrieval based on...
Numerical simulations of a single layer recurrent neural network model in which the synaptic connect...
The neural net computer simulations which will be presented here are based on the acceptance of a se...
At a first glance, artificial neural networks, with engineered learning algorithms and carefully cho...
Most theoretical studies of the computational capabilities of balanced, recurrent E/I networks assu...
One way to understand the brain is in terms of the computations it performs that allow an organism t...
We study a family of discrete-time recurrent neural network models in which the synaptic connectivit...
Chaos in dynamical systems potentially provides many different dynamical states arising from a singl...
tructure of a strange attractor in the phase space without getting stuck at local minima. This abili...
Attractor properties of a popular discrete-time neural network model are illustrated through numeric...
Abstract. It has been proposed that chaos can serve as a reservoir providing an infinite number of d...
Self-organization is thought to play an important role in structuring nervous systems. It frequently...
Self-organization is thought to play an important role in structuring nervous systems. It frequently...
AbstractIt is proposed that chaotic attractors incorporated in neural net models can represent class...
The remarkable properties of information-processing by biological and artificial neuronal networks a...
Associative memory dynamics in neural networks are generally based on attractors. Retrieval based on...