Awwal, Abdul Ahad S. | Engineering Papers

NASA NTRS1991

Trinary Associative Memory Would Recognize Machine Parts

Trinary associative memory combines merits and overcomes major deficiencies of unipolar and bipolar logics by combining them in three-valued logic that reverts to unipolar or bipolar binary selectively, as needed to perform specific tasks. Advantage of associative memory: one obtains access to all parts of it simultaneously on basis of content, rather than address, of data. Consequently, used to exploit fully parallelism and speed of optical computing.

Liu, Hua-Kuang↗

NASA NTRS1989

Machine parts recognition using a trinary associative memory

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.

Awwal, Abdul Ahad S.↗