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ENGL
2008
142views more  ENGL 2008»
13 years 7 months ago
A Solid-State Neuron for Spiking Neural Network Implementation
This paper presents a compact analog neuron cell incorporating an array of charge-coupled synapses connected via a common output terminal. The novel silicon synapse is based on a t...
Yajie Chen, Steve Hall, Liam McDaid, Octavian Buiu...
IJCNN
2007
IEEE
14 years 1 months ago
A Closed Form Solution for Multiple-Input Spike Based Adaptive Filters
— Neurons are point process systems, in the sense that the inputs and output which are spike trains can be treated as point processes. System identification of a point process s...
Il Park, António R. C. Paiva, Jose C. Princ...
NIPS
2007
13 years 9 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
NN
2007
Springer
13 years 7 months ago
Edge of chaos and prediction of computational performance for neural circuit models
We analyze in this article the significance of the edge of chaos for real-time computations in neural microcircuit models consisting of spiking neurons and dynamic synapses. We ...
Robert A. Legenstein, Wolfgang Maass
NIPS
2001
13 years 9 months ago
Spike timing and the coding of naturalistic sounds in a central auditory area of songbirds
In nature, animals encounter high dimensional sensory stimuli that have complex statistical and dynamical structure. Attempts to study the neural coding of these natural signals f...
B. D. Wright, Kamal Sen, William Bialek, A. J. Dou...