A Systematic Method for Configuring VLSI Networks of Spiking Neurons
نویسندگان
چکیده
منابع مشابه
A Systematic Method for Configuring VLSI Networks of Spiking Neurons
An increasing number of research groups are developing custom hybrid analog/digital very large scale integration (VLSI) chips and systems that implement hundreds to thousands of spiking neurons with biophysically realistic dynamics, with the intention of emulating brainlike real-world behavior in hardware and robotic systems rather than simply simulating their performance on general-purpose dig...
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Spiking neural networks implemented using electronic Very Large Scale Integration (VLSI) circuits are promising information processing architectures for carrying out complex cognitive tasks in real-world applications. These circuits are developed using standard silicon technologies, and exploit the analog properties of transistors to emulate the phenomena underlying the computations and the com...
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The computational power of formal models for networks of spiking neurons is compared with that of other neural network models based on McCulloch Pitts neurons (i.e. threshold gates) respectively sigmoidal gates. In particular it is shown that networks of spiking neurons are computationally more powerful than these other neural network models. A concrete biologically relevant function is exhibit...
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We developed a general framework to configure a spiking neuronal network so that it can precisely generate a desired spatio-temporal pattern of spikes. The unit of spiking neuronal networks employed here is a leaky integrate-and-fire model. Robustness of configured spiking neuronal network is discussed, which leads us to use some routine methods in linear-programming to solve the set of inequal...
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For a network of spiking neurons with reasonable postsynaptic potentials, we derive a supervised learning rule akin to traditional error-back-propagation, SpikeProp and show how to overcome the discontinuities introduced by thresholding. Using this learning algorithm, we demonstrate how networks of spiking neurons with biologically plausible time-constants can perform complex non-linear classif...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2011
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco_a_00182