• DocumentCode
    2449128
  • Title

    Hysteresis quantizer

  • Author

    Jin´no, Kenya ; Tanaka, Manioru

  • Author_Institution
    Sophia Univ., Tokyo, Japan
  • Volume
    1
  • fYear
    1997
  • fDate
    9-12 Jun 1997
  • Firstpage
    661
  • Abstract
    This paper proposes two type quantizers by using mutual connected neural networks. Since each cell of the neural networks has hysteresis properties, these quantizers can convert any input signals into a suitable quantization output. Also, we propose its application for image processing which can be intensity conversion. By using an area intensity method, we can get high quality output images in spite of to use bilevel output function
  • Keywords
    hysteresis; image processing; neural nets; quantisation (signal); hysteresis quantizer; image processing; intensity conversion; mutual connected neural networks; Differential equations; Hysteresis; Image converters; Image processing; Neurofeedback; Neurons; Output feedback; Quantization; State feedback;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1997. ISCAS '97., Proceedings of 1997 IEEE International Symposium on
  • Print_ISBN
    0-7803-3583-X
  • Type

    conf

  • DOI
    10.1109/ISCAS.1997.608919
  • Filename
    608919
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2449128