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[Author] Hyosig WON(1hit)

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  • Switched Diffusion Analog Memory for Neural Networks with Hebbian Learning Function and Its Linear Operation

    Hyosig WON  Yoshihiro HAYAKAWA  Koji NAKAJIMA  Yasuji SAWADA  

     
    PAPER

      Vol:
    E79-A No:6
      Page(s):
    746-751

    We have fabricated a new analog memory for integrated artificial neural networks. Several attempts have been made to develop a linear characteristics of floating-gate analog memorys with feedback circuits. The learning chip has to have a large number of learning control circuit. In this paper, we propose a new analog memory SDAM with three cascaded TFTs. The new analog memory has a simple design, a small area occupancy, a fast switching speed and an accurate linearity. To improve accurate linearity, we propose a new chargetransfer process. The device has a tunnel junction (poly-Si/poly-Si oxide/poly-Si sandwich structure), a thin-film transistor, two capacitors, and a floating-gate MOSFET. The diffusion of the charges injected through the tunnel junction are controlled by a source follower operation of a thin film transistor (TFT). The proposed operation is possible that the amounts of transferred charges are constant independent of the charges in storage capacitor.