We analyze the retrieval dynamics of analog ‘‘neural’’ networks with clocked sigmoid elements and multiple signal delays. Proving a conjecture by Marcus and Westervelt, we show that for delay-independent symmetric coupling strengths, the only attractors are fixed points and periodic limit cycles. The same result applies to a larger class of asymmetric networks that may be utilized to store temporal associations with a cyclic structure. We discuss implications for various learning schemes in the space-time domain
The paper considers a general neural network model with impulses at a given sequence of instants, di...
It is shown that if the neuronal gains are small compared with the synaptic connection weights, then...
Attractor networks are an influential theory for memory storage in brain systems. This theory has re...
We analyze the retrieval dynamics of analog ‘‘neural’’ networks with clocked sigmoid elements and mu...
We study the representation of static patterns and temporal sequences in neural networks with signal...
We have studied the basins of attraction for fixed point and oscillatory attractors in an electronic...
We show that the delayed feedback neural networks for storing limit cycles can be trained using a gl...
We propose a simple neural network model to understand the dynamics of temporal pulse coding. The mo...
Oscillatory and synchronized neural activities are commonly found in the brain, and evidence suggest...
AbstractSome sufficient conditions are obtained for the existence and global exponential stability o...
Delays are ubiquitous in biological systems, ranging from genetic regulatory networks and synaptic c...
Delays are ubiquitous in biological systems, ranging from genetic regulatory networks and synaptic c...
The persistent and graded activity often observed in cortical circuits is sometimes seen as a signat...
This research attempts to identify and model ways to store information in dynamic, chaotic neural ...
SCOPUS=eid=2-s2.0-80052989624 We study the storage and retrieval of phase-coded patterns as stable ...
The paper considers a general neural network model with impulses at a given sequence of instants, di...
It is shown that if the neuronal gains are small compared with the synaptic connection weights, then...
Attractor networks are an influential theory for memory storage in brain systems. This theory has re...
We analyze the retrieval dynamics of analog ‘‘neural’’ networks with clocked sigmoid elements and mu...
We study the representation of static patterns and temporal sequences in neural networks with signal...
We have studied the basins of attraction for fixed point and oscillatory attractors in an electronic...
We show that the delayed feedback neural networks for storing limit cycles can be trained using a gl...
We propose a simple neural network model to understand the dynamics of temporal pulse coding. The mo...
Oscillatory and synchronized neural activities are commonly found in the brain, and evidence suggest...
AbstractSome sufficient conditions are obtained for the existence and global exponential stability o...
Delays are ubiquitous in biological systems, ranging from genetic regulatory networks and synaptic c...
Delays are ubiquitous in biological systems, ranging from genetic regulatory networks and synaptic c...
The persistent and graded activity often observed in cortical circuits is sometimes seen as a signat...
This research attempts to identify and model ways to store information in dynamic, chaotic neural ...
SCOPUS=eid=2-s2.0-80052989624 We study the storage and retrieval of phase-coded patterns as stable ...
The paper considers a general neural network model with impulses at a given sequence of instants, di...
It is shown that if the neuronal gains are small compared with the synaptic connection weights, then...
Attractor networks are an influential theory for memory storage in brain systems. This theory has re...