We present more specific non-linear properties of Spike-Rate Perceptron with sub-Poisson inputs based on the diffusion approximation of renewal process, ...
Apr 25, 2024 · The non-linear properties of Spike-Rate Perceptron with sub-Poisson input. ... Identifying Kinetic Constants by the Intrinsic Properties of Markov ...
In this communication, we examine to what extent a linear-nonlinear cascade can quantitatively reproduce the firing rate dynamics of spiking neuron models. To ...
Missing: Perceptron | Show results with:Perceptron
Feb 23, 2024 · The relationship between the neuron input and output rates is non-linear, a necessary condition for proper neural network functionality.
Jul 20, 2016 · The second stage in these models is a static, nonlinear function that maps the strength of the feature in the time-varying input to an output ...
Missing: Perceptron | Show results with:Perceptron
The Non-linear Properties of Spike-Rate Perceptron with Sub-Poisson Input.........................................1974. Xuyan Xiang,Yingchun Deng, and ...
We derive a synaptic learning rule for spiking neurons that couples functional efficiency with the explanation of several well-documented biological phenomena.
Oct 22, 2024 · It is found that both schemes approximate well the input-output characteristics of spiking models such as the IF and the Hodgkin-Huxley models.
They state that a spiking neuron can learn with STDP, basically, any map from input to output spike trains that it could possibly implement in a stable manner.
Jan 12, 2017 · The output of the filters, x1, x2, ... is transformed by a nonlinearity into an instantaneous spike rate that drives an inhomogeneous Poisson ...