Editorial: Spiking Neural Network Learning, Benchmarking, Programming and Executing
نویسندگان
چکیده
منابع مشابه
Supervised Associative Learning in Spiking Neural Network
In this paper, we propose a simple supervised associative learning approach for spiking neural networks. In an excitatory-inhibitory network paradigm with Izhikevich spiking neurons, synaptic plasticity is implemented on excitatory to excitatory synapses dependent on both spike emission rates and spike timings. As results of learning, the network is able to associate not just familiar stimuli b...
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Recent neural ensemble recordings have established a link between goal-directed spatial decision making and internally generated neural sequences in the hippocampus of rats. To elucidate the synaptic mechanisms of these sequences underlying spatial decision making processes, we develop and investigate a spiking neural circuit model endowed with a combination of two synaptic plasticity mechanism...
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We have been building an auto/heteroassociative spiking neural network combined with a working memory model. In this model, a statedriven forward sequence and a goal-driven backward sequence on the associative network are respectively represented by a sequence of synchronous firing in a particular gamma subcycle during a theta oscillation. These forward and backward sequence firings are transmi...
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ARM microprocessors are found in nearly every consumer device, from smartphones to gameboxes to e-readers and digital televisions. But did you know that, combined, these same ARM microprocessor cores can simulate the human brain? The Spiking Neural Network Architecture (SpiNNaker), a massively parallel neurocomputer architecture, aims to use more than one million ARM microprocessor cores to mod...
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In this paper, learning algorithm for a single multiplicative spiking neuron (MSN) is proposed and tested for various applications where a multilayer perceptron (MLP) neural network is conventionally used. It is found that a single MSN is sufficient for the applications that require a number of neurons in different hidden layers of a conventional neural network. Several benchmark and real-life ...
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ژورنال
عنوان ژورنال: Frontiers in Neuroscience
سال: 2020
ISSN: 1662-453X
DOI: 10.3389/fnins.2020.00276