標題: Multi-input Silicon Neuron with Weighting Adaptation
作者: Li, Ming-Ze
Ping-Wang, Po
Tang, Kea-Tiong
Fang, Wai-Chi
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
公開日期: 2009
摘要: This paper presents a biologically inspired "integrate-and-fire (I&F) neuron" which has multiple input dendrites for adaptive weight storage. By using a capacitor-free integrator, longer time constant and smaller chip area can be achieved. A low-power Schmitt Trigger is used to implement the feedback loop to achieve smaller power consumption. Weights are stored by using floating gate MOS transistors as nonvolatile analog memory. Simulation results show that this I&F neuron can be utilized in an analog VLSI neural network system.
URI: http://hdl.handle.net/11536/134952
ISBN: 978-1-4244-4292-8
期刊: 2009 IEEE/NIH LIFE SCIENCE SYSTEMS AND APPLICATIONS WORKSHOP
起始頁: 194
結束頁: +
Appears in Collections:Conferences Paper