Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits (Record no. 81068)
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fixed length control field | 03950nam a22006255i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-319-57081-5 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20220801222715.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 170424s2017 sz | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783319570815 |
-- | 978-3-319-57081-5 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 621.382 |
100 1# - AUTHOR NAME | |
Author | Florescu, Dorian. |
245 10 - TITLE STATEMENT | |
Title | Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2017. |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | XIV, 139 p. 42 illus., 27 illus. in color. |
490 1# - SERIES STATEMENT | |
Series statement | Springer Theses, Recognizing Outstanding Ph.D. Research, |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | Nomenclature -- 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 ## - SUMMARY, ETC. | |
Summary, etc | 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 a linear filter, given the input of the filter encoded with the same neuron model. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | https://doi.org/10.1007/978-3-319-57081-5 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
264 #1 - | |
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-- | Springer International Publishing : |
-- | Imprint: Springer, |
-- | 2017. |
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-- | computer |
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-- | online resource |
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Signal processing. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Neural networks (Computer science) . |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Neurosciences. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | System theory. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Control theory. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Electronic circuits. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Signal, Speech and Image Processing . |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Mathematical Models of Cognitive Processes and Neural Networks. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Neuroscience. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Systems Theory, Control . |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Electronic Circuits and Systems. |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
-- | 2190-5061 |
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-- | ZDB-2-ENG |
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-- | ZDB-2-SXE |
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