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Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits. 1st ed. 2017
・ISBN 978-3-319-57080-8 hard EUR 99.99
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| 著者・編者 | Florescu, Dorian, |
|---|---|
| シリーズ | (Springer Theses) |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2017 |
| ページ数 | 139 pp. |
| 言語 | ENG |
| ニュース番号 | <A05-57250> |
解説
This work is motivated by the ongoing open question of how information in the outside world is represented and processed by the brain. Consequently, several novel methods are developed.
A new mathematical formulation is proposed for the encoding and decoding of analog signals using integrate-and-fire neuron models. Based on this formulation, a novel algorithm, significantly faster than the state-of-the-art method, is proposed for reconstructing the input of the neuron.
Two new identification methods are proposed for neural circuits comprising a filter in series with a spiking neuron model. These methods reduce the number of assumptions made by the state-of-the-art identification framework, allowing for a wider range of models of sensory processing circuits to be inferred directly from input-output observations.
A third contribution is an algorithm that computes the spike time sequence generated by an integrate-and-fire neuron model in response to the output of alinear filter, given the input of the filter encoded with the same neuron model.