• DocumentCode
    1749229
  • Title

    Multi-pattern real-valued spectral associative memories

  • Author

    Spencer, R.G.

  • Author_Institution
    Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1180
  • Abstract
    A multi-pattern encoding and decoding scheme is presented that extends the family of spectral associative memories (SAMs) to include gray-level, or analog patterns. SAMs are frequency-domain formulations of associative memory that combine the extrinsic redundancy of neural networks with the in-phase, quadrature, and complex modulation schemes of communications. Considerable coding gain occurs at the level of modulation and these networks may be regarded as multi-channel, multi-carrier generalizations of amplitude modulation. Unlike multi-pattern bipolar SAMs, which are exclusively content-addressable, real-valued SAMs also have an addressable mode in which the recall of a particular memory may be forced. Band structures and anti-aliasing constraints are presented along with a probabilistic formulation in which virtual entanglement is a natural feature. Simulations are presented that demonstrate dual-memory recall for 6×6 gray-level patterns
  • Keywords
    content-addressable storage; decoding; eigenvalues and eigenfunctions; encoding; frequency-domain analysis; neural nets; probability; singular value decomposition; amplitude modulation; anti-aliasing constraints; decoding; eigenvalues; frequency-domain analysis; gray-level; multiple-pattern encoding; neural networks; probability; singular value decomposition; spectral associative memories; Active appearance model; Amplitude modulation; Associative memory; Convolution; Decoding; Eigenvalues and eigenfunctions; Frequency domain analysis; Modulation coding; Neural networks; Nonvolatile memory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7044-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2001.939528
  • Filename
    939528