Machine Parts Recognition Using A Trinary Associative Memory

Abdul Ahad S. Awwal; Mohammad A Karim; Hua-Kuang Liu

doi:10.1117/12.7976994

1 May 1989 Machine Parts Recognition Using A Trinary Associative Memory

Abdul Ahad S. Awwal; Mohammad A Karim; Hua-Kuang Liu;

Author Affiliations +

Optical Engineering, 28(5), 285537 (1989). https://doi.org/10.1117/12.7976994

Abstract

The convergence mechanism of vectors in Hopfield's neural network in relation to recognition of partially known patterns is studied in terms of both inner products and Hamming distance. It has been shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, inner product weighting coefficients play a more dominant role in certain data representations for determining the convergence mechanism. A trinary neuron representation for associative memory is found to be more effective for associative recall. Applications of the trinary associative memory to reconstruct machine part images that are partially missing are demonstrated by means of computer simulation as examples of the usefulness of this approach.

Citation Download Citation

Abdul Ahad S. Awwal, Mohammad A Karim, Hua-Kuang Liu, "Machine Parts Recognition Using A Trinary Associative Memory," Optical Engineering 28(5), 285537 (1 May 1989). https://doi.org/10.1117/12.7976994 . Submission:

ACCESS THE FULL ARTICLE

PERSONAL SIGN IN
Full access may be available with your subscription

Email or Username Forgot your username?

Password Forgot your password?

Show

Remember Email/Username on this computer

Remember Password

No SPIE account? Create an account
or Institutional Sign In via Shibboleth

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $20.00

Non-members: $25.00 ADD TO CART

Keywords/Phrases

Search In:

Publication Years