• DocumentCode
    1161444
  • Title

    Analog electronic cochlea design using multiplexing switched-capacitor circuits

  • Author

    Bor, Jenn-Chyou ; Wu, Chung-Yu

  • Author_Institution
    Dept. of Electron. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
  • Volume
    7
  • Issue
    1
  • fYear
    1996
  • fDate
    1/1/1996 12:00:00 AM
  • Firstpage
    155
  • Lastpage
    166
  • Abstract
    A new design methodology is proposed to realize a real cochlea using the multiplexing switched-capacitor circuits. The proposed technique is based upon the transmission-line model proposed by Zwislocki (1950). At the cost of the increase in the number of clock phases, the decay rate in the transition region of the filter section can be increased by adding only a few components. Therefore, the components and chip area of the designed silicon cochlea can be small. An experimental chip containing four filter sections has been designed and fabricated. The measured frequency responses from the 32-section cochlea formed by cascading nine fabricated chips are consistent with both theoretical calculation results and observed behavior of a real cochlea. Moreover, the designed silicon cochlea has the dynamic range of 67 dB in each section and a low sensitivity to process variations. Thus it is suitable for VLSI implementation with the associated neural network
  • Keywords
    VLSI; analogue processing circuits; cascade networks; frequency response; multiplexing; multiplexing equipment; neural chips; physiological models; speech recognition; switched capacitor filters; transmission line theory; analog electronic cochlea; associated neural network; auditory nervous systems; filter; frequency responses; multiplexing switched-capacitor circuits; partial differential equations; speech recognition; transmission-line model; Clocks; Costs; Design methodology; Dynamic range; Filters; Frequency measurement; Semiconductor device measurement; Silicon; Switched capacitor circuits; Transmission lines;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/72.478400
  • Filename
    478400