CIVILICA We Respect the Science
Publisher of Iranian Journals and Conference Proceedings

MNIST Recognition Using Unsupervised Biologically Learning

Credit to Download: 1 | Page Numbers 12 | Abstract Views: 129

How to Download This Paper

For Downloading the Fulltext of CIVILICA papers please visit the orginal Persian Section of website.

Authors MNIST Recognition Using Unsupervised Biologically Learning

  Soheila Nazari - Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
  Karim faez - Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran


In this paper, spiking neural networks (SNN) inspired by the model of local cortical population as a biologicalneuro-computing resource for digit recognition was presented. SNN was equipped with spike-based unsupervisedweight optimization based on the dynamical behavior of the excitatory (AMPA) and inhibitory (GABA) synapsesusing Spike Timing Dependent Plasticity (STDP). There are two main reasons why this structure is state of the artcompared to previous works: learning process is compatible with many experimental observations on induction oflong-term potentiation and long-term depression, image to signal mapping created an informative signal of theimage based on sequences of prolate spheroidal wave functions (PSWFs). Cortical SNN compared toearlier related studies recognized MNIST digits more accurate and achieved 96.1% classificationaccuracy with unsupervised learning based on sparse spike activity.


Spiking Neural Network, STDP, MNIST Recognition, Biologically Learning

Perma Link
COI code: ECMECONF01_001

how to cite to this paper:

If you want to refer to this article in your research, you can easily use the following in the resources and references section:
Nazari, Soheila & Karim faez, 2018, MNIST Recognition Using Unsupervised Biologically Learning, The first national conference on applied research in electrical engineering, computer science and medical engineering, شيروان, موسسه پژوهشي رهجويان پايا شهر اترك, the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Nazari, Soheila & Karim faez, 2018)
Second and more: (Nazari & faez, 2018)
For a complete overview of how to citation please review the following CIVILICA Guide (Citation)


The University/Research Center Information:
Type: state university
Paper No.: 19748
in University Ranking and Scientometrics the Iranian universities and research centers are evaluated based on scientific papers.

Research Info Management

Export Citation info of this paper to research management softwares

New Related Papers

Iran Scientific Advertisment Netword

Share this paper


COI is a national code dedicated to all Iranian Conference and Journal Papers. the COI of each paper can be verified online.