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Computing with spiking neurons

Author:

Wolfgang MaassAuthors Info & Claims

Pulsed neural networks

February 1999

Pages 55 - 85

Published: 01 February 1999 Publication History

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Almomani AAlauthman MAlweshah MDorgham OAlbalas F(2019)A comparative study on spiking neural network encoding schemaCluster Computing10.1007/s10586-018-02891-022:2(419-433)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s10586-018-02891-0
RhéAume FGrenier DBossé í(2011)Multistate combination approaches for liquid state machine in supervised spatiotemporal pattern classificationNeurocomputing10.1016/j.neucom.2011.03.03374:17(2842-2851)Online publication date: 1-Oct-2011
https://dl.acm.org/doi/10.1016/j.neucom.2011.03.033
Tang DKubota N(2010)Human localization by fuzzy spiking neural network based on informationally structured spaceProceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I10.5555/1939659.1939664(25-32)Online publication date: 22-Nov-2010
https://dl.acm.org/doi/10.5555/1939659.1939664
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Computing with spiking neurons

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Electrophysiological measurements in the locust antennal lobe have suggested that the odor could be encoded spatially and temporally during the network oscillation in the firing patterns of the excitatory cells. Interested by the mechanisms responsible ...
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We consider a threshold-crossing spiking process as a simple model for the activity within a population of neurons. Assuming that these neurons are driven by a common fluctuating input with gaussian statistics, we evaluate the cross-correlation of spike ...

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Published In

Pulsed neural networks

February 1999

371 pages

ISBN:0626133504

Editors:
Wolfgang Maass
Technische Univ. Graz, Graz, Austria
,
Christopher M. Bishop
Univ. of Edinburgh, Edinburgh, Scotland, UK

Publisher

MIT Press

Cambridge, MA, United States

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Published: 01 February 1999

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Almomani AAlauthman MAlweshah MDorgham OAlbalas F(2019)A comparative study on spiking neural network encoding schemaCluster Computing10.1007/s10586-018-02891-022:2(419-433)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s10586-018-02891-0
RhéAume FGrenier DBossé í(2011)Multistate combination approaches for liquid state machine in supervised spatiotemporal pattern classificationNeurocomputing10.1016/j.neucom.2011.03.03374:17(2842-2851)Online publication date: 1-Oct-2011
https://dl.acm.org/doi/10.1016/j.neucom.2011.03.033
Tang DKubota N(2010)Human localization by fuzzy spiking neural network based on informationally structured spaceProceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I10.5555/1939659.1939664(25-32)Online publication date: 22-Nov-2010
https://dl.acm.org/doi/10.5555/1939659.1939664
Pearson MGilhespy IGurney KMelhuish CMitchinson BNibouche MPipe A(2005)A real-time, FPGA based, biologically plausible neural network processorProceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II10.5555/1986079.1986260(1021-1026)Online publication date: 11-Sep-2005
https://dl.acm.org/doi/10.5555/1986079.1986260
Häfliger PAasebø E(2004)A Rank EncoderAnalog Integrated Circuits and Signal Processing10.1023/B:ALOG.0000031432.51988.1740:1(39-51)Online publication date: 1-Jul-2004
https://dl.acm.org/doi/10.1023/B%3AALOG.0000031432.51988.17
Natschlüer TRuf BSchmitt M(2001)Unsupervised learning and self-organization in networks of spiking neuronsSelf-Organizing neural networks10.5555/505763.505766(45-73)Online publication date: 1-Jun-2001
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Computing with spiking neurons

Encoding in a network of sparsely connected spiking neurons: application to locust olfaction

Stimulus-dependent correlations in threshold-crossing spiking neurons

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