We propose a novel associative memory model wherein the neural activity without an input (i.e., spontaneous activity) is modified by an input to generate a target response that is memorized for recall upon the same input. Suitable design of synaptic connections enables the model to memorize input/output (I/O) mappings equaling 70% of the total number of neurons, where the evoked activity distinguishes a target pattern from others. Spontaneous neural activity without an input shows chaotic dynamics but keeps some similarity with evoked activities, as reported in recent experimental studies
Human memory is associative and emerges from the behaviour of neurons. Two models, based on commonly...
金沢大学理工研究域電子情報学系A model of dynamic associative memories is proposed in this paper. The aim is to find...
The persistent and graded activity often observed in cortical circuits is some-times seen as a signa...
Recent experimental measurements have demonstrated that spontaneous neural activity in the absence o...
Learning is a process that helps create neural dynamical systems so that an appropriate output patte...
Learning is a process that helps create neural dynamical systems so that an appropriate output patte...
Introduction The associative memory is one of the fundamental algorithms of information processing ...
A neural model for the recovery of learnt patterns is presented. The model simulates the theta-gamma...
This paper proposes a novel neural network model for associative memory using dynamical systems. The...
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...
We describe a modified attractor neural network in which neuronal dynamics takes place on a time sca...
We developed a cooperative model of the cortical column incorporating an idealized subunit, the trio...
The persistent and graded activity often observed in cortical circuits is sometimes seen as a signat...
In this paper, we present a neural network system related to about memory and recall that consists o...
Human memory is associative and emerges from the behaviour of neurons. Two models, based on commonly...
金沢大学理工研究域電子情報学系A model of dynamic associative memories is proposed in this paper. The aim is to find...
The persistent and graded activity often observed in cortical circuits is some-times seen as a signa...
Recent experimental measurements have demonstrated that spontaneous neural activity in the absence o...
Learning is a process that helps create neural dynamical systems so that an appropriate output patte...
Learning is a process that helps create neural dynamical systems so that an appropriate output patte...
Introduction The associative memory is one of the fundamental algorithms of information processing ...
A neural model for the recovery of learnt patterns is presented. The model simulates the theta-gamma...
This paper proposes a novel neural network model for associative memory using dynamical systems. The...
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...
We describe a modified attractor neural network in which neuronal dynamics takes place on a time sca...
We developed a cooperative model of the cortical column incorporating an idealized subunit, the trio...
The persistent and graded activity often observed in cortical circuits is sometimes seen as a signat...
In this paper, we present a neural network system related to about memory and recall that consists o...
Human memory is associative and emerges from the behaviour of neurons. Two models, based on commonly...
金沢大学理工研究域電子情報学系A model of dynamic associative memories is proposed in this paper. The aim is to find...
The persistent and graded activity often observed in cortical circuits is some-times seen as a signa...