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Based on the information processing functionalities of spiking neurons, a spiking neural network model is proposed to extract features from a visual image. The network is constructed with a conductance-based integrate-and-fire neuron model and a set of specific receptive fields. The properties of the network are detailed in this paper. Simulation results show that the network is able to perform image feature extraction within a time interval of 100 ms. This processing time is consistent with the human visual system. The demonstrations show how the network can extract right-angle contours in a visual image. Based on this principle, many other image features can be extracted by analogy. The parallel processing mechanism of this network model is very promising for a hardware implementation based on VLSI or FPGA technology.
Update : 2025-04-26 Size : 282kb Publisher : sacoura31

spiking neural network
Update : 2025-04-26 Size : 8kb Publisher : ali

神经元网络延时反馈程序,证明局部神经元延时反馈可以激发周围神经元产生spiking放电或bursting放电-Delayed feedback neural network program, proof of local neuronal delayed feedback can stimulate peripheral neurons spiking discharge or bursting
Update : 2025-04-26 Size : 1kb Publisher : wuxinyi

spiking neural network and fpga implementation
Update : 2025-04-26 Size : 5.16mb Publisher : wangl

Tempotron算法简单实现,Spiking神经网络初学,实现的学习算法-Tempotron algorithm is simple to achieve, Spiking Neural Network beginner to achieve learning algorithm
Update : 2025-04-26 Size : 1kb Publisher : 高国明

This GUi implements the Eugene Izhikevich (2003) spiking equation. Spiking Neurons simulator Easily Simulate a Customizable Network of Spiking Leaky Integrate and Fire Neurons Simulation of an STDP-based constructive algorithm for spiking neural networks The Siegert Neuron has a transfer function equivalent to a leaky integrate-and-fire neuron.
Update : 2025-04-26 Size : 770kb Publisher : Sina

DL : 0
In order to account for the rapidity of visual processing, we explore visual coding strategies using a one-pass feed-forward spiking neural network.We based our model on the work of Van Rullen and Thorpe, which constructs a retinal representation and transmission using an orthogonal wavelet transform and which is transformed into a spike code thanks to a rank order coding scheme which provides an alternative to the classical spike frequency coding scheme.
Update : 2025-04-26 Size : 205kb Publisher : sacoura

DL : 0
document for Encoding Spike Patterns in Multilayer Spiking Neural Networks
Update : 2025-04-26 Size : 2.52mb Publisher : saeed92
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