Publication detail

Constructing Hierarchical Neural Nets Using Sparse Distributed Memory

GREBENÍČEK, F.

Original Title

Constructing Hierarchical Neural Nets Using Sparse Distributed Memory

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

This paper discusses a possibility of the hierarchical neural nets construction using Kanerva's Sparse Distributed Memory (SDM). SDM is an associative neural memory and can be used in visual pattern recognition. The paper introduces a hierarchical net for digit recognition. Results of xperiment show notable properties of the net: insensivity to digit position and warping. Finally, a possible modification of Fukushima's Neocognitron is discussed.

Keywords

Neural nets, associative memory, Sparse Distributed Memory, pattern recognition

Authors

GREBENÍČEK, F.

Released

1. 1. 2000

Location

Sv. Hostýn, Bystřice pod Hostýnem

ISBN

80-85988-51-8

Book

ASIS 2000 Proceedings of the Colloquium

Pages from

359

Pages to

364

Pages count

6

URL

http://www.fit.vutbr.cz/~grebenic/Publikace/asis2000.ps.zip

BibTex

@inproceedings{BUT192151,
  author="František {Grebeníček}",
  title="Constructing Hierarchical Neural Nets Using Sparse Distributed Memory",
  booktitle="ASIS 2000 Proceedings of the Colloquium",
  year="2000",
  pages="359--364",
  address="Sv. Hostýn, Bystřice pod Hostýnem",
  isbn="80-85988-51-8",
  url="http://www.fit.vutbr.cz/~grebenic/Publikace/asis2000.ps.zip"
}