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The brain-inspired spiking neurons are more biologically plausible and computationally powerful than traditional rate-based artificial neurons. Most of the existing spiking neuron based applications assume noise-free condition for learning and testing. However, noise widely exists in the network of spiking neurons and the neural response can be significantly disturbed by different types of noise....
With a similar capability of processing spikes as biological neural systems, networks of spiking neurons are expected to achieve a performance similar to that of living brains. In recent days, many great achievements have been made in spiking neuron models and its learning algorithm. We build an integrated model using spiking neural networks (SNNs), which performs phase encoding method and delay learning-based...
Pulse-Coupled Neural Network is known as third generation artificial neural network. It is created by visual cortex neurons, a synchronous pulse release phenomenon of mammals. Compare to traditional artificial neural network, PCNN has the characteristics of dynamic neural network, integrated space-time, automatic propagation and synchronous pulse release. PCNN has tendency for image retention information...
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