000 | 03950nam a22006255i 4500 | ||
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001 | 978-3-319-57081-5 | ||
003 | DE-He213 | ||
005 | 20220801222715.0 | ||
007 | cr nn 008mamaa | ||
008 | 170424s2017 sz | s |||| 0|eng d | ||
020 |
_a9783319570815 _9978-3-319-57081-5 |
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024 | 7 |
_a10.1007/978-3-319-57081-5 _2doi |
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050 | 4 | _aTK5102.9 | |
072 | 7 |
_aTJF _2bicssc |
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_aUYS _2bicssc |
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_aTJF _2thema |
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_aUYS _2thema |
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_a621.382 _223 |
100 | 1 |
_aFlorescu, Dorian. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _962913 |
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245 | 1 | 0 |
_aReconstruction, Identification and Implementation Methods for Spiking Neural Circuits _h[electronic resource] / _cby Dorian Florescu. |
250 | _a1st ed. 2017. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2017. |
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300 |
_aXIV, 139 p. 42 illus., 27 illus. in color. _bonline resource. |
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_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aSpringer Theses, Recognizing Outstanding Ph.D. Research, _x2190-5061 |
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505 | 0 | _aNomenclature -- Acronyms -- 1 Introduction -- 2 Time Encoding and Decoding in Bandlimited and Shift-Invariant Spaces -- 3 A Novel Framework for Reconstructing Bandlimited Signals Encoded by Integrate and-Fire Neurons -- 4 A Novel Reconstruction Framework in Shift-Invariant Spaces for Signals Encoded with Integrate-and-Fire Neurons -- 5 A New Approach to the Identification of Sensory Processing Circuits Based on Spiking Neuron Data -- 6 A New Method for Implementing Linear Filters in the Spike Domain -- 7 Conclusions and Future Work -- Bibliography. | |
520 | _aThis 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 a linear filter, given the input of the filter encoded with the same neuron model. | ||
650 | 0 |
_aSignal processing. _94052 |
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650 | 0 |
_aNeural networks (Computer science) . _962914 |
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650 | 0 |
_aNeurosciences. _924499 |
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650 | 0 |
_aSystem theory. _93409 |
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650 | 0 |
_aControl theory. _93950 |
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650 | 0 |
_aElectronic circuits. _919581 |
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650 | 1 | 4 |
_aSignal, Speech and Image Processing . _931566 |
650 | 2 | 4 |
_aMathematical Models of Cognitive Processes and Neural Networks. _932913 |
650 | 2 | 4 |
_aNeuroscience. _934310 |
650 | 2 | 4 |
_aSystems Theory, Control . _931597 |
650 | 2 | 4 |
_aElectronic Circuits and Systems. _962915 |
710 | 2 |
_aSpringerLink (Online service) _962916 |
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773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783319570808 |
776 | 0 | 8 |
_iPrinted edition: _z9783319570822 |
776 | 0 | 8 |
_iPrinted edition: _z9783319860725 |
830 | 0 |
_aSpringer Theses, Recognizing Outstanding Ph.D. Research, _x2190-5061 _962917 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-57081-5 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
942 | _cEBK | ||
999 |
_c81068 _d81068 |