A Learning Algorithm for a Neural Network LSI with Restricted Integer Weights (Special Issue on New Concept Device and Novel Architecture LSIs)

スポンサーリンク

概要

• 論文の詳細を見る

• A novel learning algorithm for a neural network LSI which has low resolution synapse weights is proposed. Following a brief discussion of the synapse weight adaptation mechanism in the gradient descent scheme, we propose a way of achieving relaxation from the influence of discretized weight. Restriction of the number of synapses to be updated in one learning iteration is effective to relax the influence. Simulation results support the effectiveness of this learning algorithm. Low resolution synapses will be practical to realize large-scale neural network LSIs.

• 社団法人電子情報通信学会の論文
• 1997-07-25

著者

• Shima T

  Toshiba Research And Development Center

• KIMURA Tomohisa

  Toshiba Research and Development Center

• SHIMA Takeshi

  Toshiba Research and Development Center

関連論文

• A Learning Algorithm for a Neural Network LSI with Restricted Integer Weights (Special Issue on New Concept Device and Novel Architecture LSIs)

スポンサーリンク