Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF

Implementation of a neuron like information processing structure at hardware level is a burning research problem. In this article, we analyze the modified hybrid spiking neuron model (the MHSN model) in distributed delay framework (DDF) for hardware level implementation point of view. We investigate...

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Main Authors: Saket Kumar Choudhary, Karan Singh
Format: Article
Language:English
Published: Universidad Internacional de La Rioja (UNIR) 2016-12-01
Series:International Journal of Interactive Multimedia and Artificial Intelligence
Subjects:
Online Access:http://www.ijimai.org/journal/node/1444
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author Saket Kumar Choudhary
Karan Singh
author_facet Saket Kumar Choudhary
Karan Singh
author_sort Saket Kumar Choudhary
collection DOAJ
description Implementation of a neuron like information processing structure at hardware level is a burning research problem. In this article, we analyze the modified hybrid spiking neuron model (the MHSN model) in distributed delay framework (DDF) for hardware level implementation point of view. We investigate its temporal information processing capability in term of inter-spike-interval (ISI) distribution. We also perform the stability analysis of the MHSN model, in which, we compute nullclines, steady state solution, eigenvalues corresponding the MHSN model. During phase plane analysis, we notice that the MHSN model generates limit cycle oscillations which is an important phenomenon in many biological processes. Qualitative behavior of these limit cycle does not changes due to the variation in applied input stimulus, however, delay effect the spiking activity and duration of cycle get altered.
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spelling doaj.art-2922713cf13647f880dfb0bf119010422022-12-21T20:03:47ZengUniversidad Internacional de La Rioja (UNIR)International Journal of Interactive Multimedia and Artificial Intelligence1989-16601989-16602016-12-0142404510.9781/ijimai.2016.428ijimai.2016.428Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDFSaket Kumar ChoudharyKaran SinghImplementation of a neuron like information processing structure at hardware level is a burning research problem. In this article, we analyze the modified hybrid spiking neuron model (the MHSN model) in distributed delay framework (DDF) for hardware level implementation point of view. We investigate its temporal information processing capability in term of inter-spike-interval (ISI) distribution. We also perform the stability analysis of the MHSN model, in which, we compute nullclines, steady state solution, eigenvalues corresponding the MHSN model. During phase plane analysis, we notice that the MHSN model generates limit cycle oscillations which is an important phenomenon in many biological processes. Qualitative behavior of these limit cycle does not changes due to the variation in applied input stimulus, however, delay effect the spiking activity and duration of cycle get altered.http://www.ijimai.org/journal/node/1444AnalysisDynamical SystemEigen ValueNeural Network
spellingShingle Saket Kumar Choudhary
Karan Singh
Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF
International Journal of Interactive Multimedia and Artificial Intelligence
Analysis
Dynamical System
Eigen Value
Neural Network
title Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF
title_full Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF
title_fullStr Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF
title_full_unstemmed Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF
title_short Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF
title_sort temporal information processing and stability analysis of the mhsn neuron model in ddf
topic Analysis
Dynamical System
Eigen Value
Neural Network
url http://www.ijimai.org/journal/node/1444
work_keys_str_mv AT saketkumarchoudhary temporalinformationprocessingandstabilityanalysisofthemhsnneuronmodelinddf
AT karansingh temporalinformationprocessingandstabilityanalysisofthemhsnneuronmodelinddf