Simulation of chaotic EEG patterns with a dynamic model of the olfactory system
Biological Cybernetics
Associative memories with short-range, higher order couplings
Neural Networks
Capacity of associative memory using a nonmonotonic neuron model
Neural Networks
1994 Special Issue: Biological plausibility of synaptic associative memory models
Neural Networks - Special issue: models of neurodynamics and behavior
1994 Special Issue: A biologically based model of functional properties of the hippocampus
Neural Networks - Special issue: models of neurodynamics and behavior
A network of chaotic elements for information processing
Neural Networks
Image segmentation based on oscillatory correlation
Neural Computation
Associative dynamics in a chaotic neural network
Neural Networks
A combined evolution method for associative memory networks
Neural Networks
A proposed name for aperiodic brain activity: stochastic chaos
Neural Networks
A System for Person-Independent Hand Posture Recognition against Complex Backgrounds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Synapses as dynamic memory buffers
Neural Networks
IEEE Transactions on Computers
Synchronization and desynchronization in a network of locally coupled Wilson-Cowan oscillators
IEEE Transactions on Neural Networks
Locally excitatory globally inhibitory oscillator networks
IEEE Transactions on Neural Networks
A Chaotic Feature Extracting BAM and Its Application in Implementing Memory Search
Neural Processing Letters
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In the past few decades, neural networks have been extensively adopted in various applications ranging from simple synaptic memory coding to sophisticated pattern recognition problems such as scene analysis and robot vision. Moreover, current studies on neuroscience and physiology have reported that in a typical scene segmentation problem our major senses of perception (e.g. vision, olfaction, etc.) are highly chaotic and involved non-linear neural dynamics and oscillations. In this paper, the author proposes an innovative chaotic neural oscillator-namely the Lee-oscillator (Lee's Chaotic Neural Oscillator) to provide a chaotic neural coding and information processing scheme. To illustrate the capability of Lee-oscillators upon pattern association, a chaotic auto-associative network, namely Lee-Associator (Lee's Chaotic Auto-associator) is constructed. Different from classical auto-associators such as the celebrated Hopfield network, which provides time-independent and static pattern association scheme, the Lee-Associator provides a remarkable progressive memory association scheme (what the author called 'Progressive Memory Recalling Scheme, PMRS') during the chaotic memory association. This is exactly consistent with the latest research in psychiatry and perception psychology on dynamic memory recalling schemes, as well as the implications and analogues to human perception as illustrated by the remarkable Rubin-vase experiment on visual psychology.