Published February 29, 2020 | Version v1
Journal article Open

Using Derived kernel as a new Method for Recognition a Similarity Learning.

  • 1. department of Mathematics, Jouf University, Gurayat, Saudi Arabia.
  • 2. department of Mathematics, Majmaah University, Majmaah 11952, Saudi Arabia.
  • 3. Computer Technology department, Tabuk College of Technical, Tabuk, Saudi Arabia
  • 4. College of Computer snd Information Sciences, Jouf University, Skaka, Aljouf, Saudi Arabia.
  • 1. Publisher

Description

A new technique for feature withdrawal by neural response is going to be familiarized in this research work by merging an entropy measure with Squared Pearson correlation Coefficient (SPCC) method. The process of choosing effective models on the basis of entropy measures was proposed further to enhance the ability to select templates. For more accurate similarity measure we used the statistical significant relationship between functions. The research illustrate that the proposed method is proficiently compared with the state-of-the-art methods.

Files

C5705029320.pdf

Files (1.2 MB)

Name Size Download all
md5:7b6e3fb3fc58bf09ba28fa2a253714b4
1.2 MB Preview Download

Additional details

Related works

Is cited by
Journal article: 2249-8958 (ISSN)

Subjects

ISSN
2249-8958
Retrieval Number
C5705029320/2020©BEIESP