Fundamental Analysis of a Digital Spiking Neuron for Its Spike-Based Coding
Neural Information Processing
Artificial Spiking Neurons and Analog-to-Digital-to-Analog Conversion
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Consistency in a Chaotic Spiking Oscillator
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
A Pulse-Coupled Network of SOM
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A novel hybrid spiking neuron: response analysis and learning potential
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Bifurcation and windows in a simple piecewise linear chaotic spiking neuron
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Bifurcation between superstable periodic orbits and chaos in a simple spiking circuit
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Complex oscillation-based test and its application to analog filters
IEEE Transactions on Circuits and Systems Part I: Regular Papers - Special issue on ISCAS 2009
A novel hybrid spiking neuron: bifurcations, responses, and on-chip learning
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Theoretical analysis of various synchronizations in pulse-coupled digital spiking neurons
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Synchronization via multiplex spike-trains in digital pulse coupled networks
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Synchronization of hopfield like chaotic neural networks with structure based learning
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
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This paper studies a pulse-coupled network consisting of simple chaotic spiking oscillators (CSOs). If a unit oscillator and its neighbor(s) have (almost) the same parameter values, they exhibit in-phase synchronization of chaos. As the parameter values differ, they exhibit asynchronous phenomena. Based on such behavior, some synchronous groups appear partially in the network. Typical phenomena are verified in the laboratory via a simple test circuit. These phenomena can be evaluated numerically by using an effective mapping procedure. We then apply the proposed network to image segmentation. Using a lattice pulse-coupled network via grouping synchronous phenomena, the input image data can be segmented into some sub-regions.