Analysis of Statistical Neurodynamics for the Effects of the Hysteretic Property on the Performance of Sequential Associative Neural Nets 


Vol. 4,  No. 4, pp. 1035-1045, Apr.  1997
10.3745/KIPSTE.1997.4.4.1035


PDF
  Abstract

In this important to understand how we can deal with elements for the modeling of neural networks when we are investigating the dynamical performance and the information processing capabilities. The information processing capabilities of model neural networks will change for different response, synaptic weights or learning rules. Using the statistical neurodynamics method, we evaluate the capabilities of neural networks in order to understand the basic concept of parallel distributed processing. In this paper, we explain the results of theoretical analysis of the effects of the hysteretic property on the performance of sequential associative neural networks.

  Statistics
  Cite this article

[IEEE Style]

K. E. Soo and O. C. Suk, "Analysis of Statistical Neurodynamics for the Effects of the Hysteretic Property on the Performance of Sequential Associative Neural Nets," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 4, no. 4, pp. 1035-1045, 1997. DOI: 10.3745/KIPSTE.1997.4.4.1035.

[ACM Style]

Kim Eung Soo and Oh Choon Suk. 1997. Analysis of Statistical Neurodynamics for the Effects of the Hysteretic Property on the Performance of Sequential Associative Neural Nets. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 4, 4, (1997), 1035-1045. DOI: 10.3745/KIPSTE.1997.4.4.1035.

Forms

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)

Old Journals

Indexing

All publications of TKIPS is indexed in DOI, EBSCO, Google Scholar, Crossref, and CrossCheck.

TKIPS is also selected as the Journal for Accreditation by NRF (National Research Foundation of Korea).

Related Journals