01505nas a2200217   4500000000100000000000100001008004100002260001200043653001300055653001900068653002100087653001600108100002600124700001600150245009100166856009800257300001000355490000600365520090200371022001401273       2016                            d  c12/201610aAnalysis10aNeural Network10aDynamical System10aEigen Value1 aSaket Kumar Choudhary1 aKaran Singh00aTemporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF  uhttp://www.ijimai.org/journal/sites/default/files/files/2016/11/ijimai20164_2_7_pdf_14081.pdf  a40-450 v43 aImplementation 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.  a1989-1660