Accession Number : ADA256621


Title :   Analog Very Large Scale Integration (VLSI) Implementations of Artificial Neural Networks


Descriptive Note : Rept. for Oct 1991-Apr 1992


Corporate Author : ROME LAB ROME NY


Personal Author(s) : Hinman, Michael L


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a256621.pdf


Report Date : Sep 1992


Pagination or Media Count : 38


Abstract : There has been a recent resurgence of interest in the multi- disciplinary field of artificial neural networks. Artificial neural networks, originally inspired by the computational capabilities of the human brain, refer to a variety of computing architectures that consist of massively parallel interconnections of simple processing elements. Currently, there exist two promising advanced technologies for implementing neural networks: Very Large Scale Integrated (VLSI) circuits and optical. This final technical report describes the utilization of VLSI circuits for implementing various neural networks, with an emphasis on analog VLSI. A comparison of the different implementation techniques is provided, as is the type of paradigm implemented (e.g., backpropagation, hopfield, bidirectional associative memories, etc.). Artificial Neural Networks, Analog VLSI.


Descriptors :   *NEURAL NETS , *VERY LARGE SCALE INTEGRATION , *ANALOGS , BRAIN , NETWORKS , CIRCUITS , ARCHITECTURE , SCALE , HUMANS , PROCESSING , COMPARISON


Subject Categories : Electrical and Electronic Equipment
      Computer Systems
      Bionics


Distribution Statement : APPROVED FOR PUBLIC RELEASE