神经形态工程学
计算机科学
超大规模集成
经典条件反射
炸薯条
条件作用
消光(光学矿物学)
功率消耗
人工智能
功率(物理)
嵌入式系统
人工神经网络
物理
电信
统计
光学
量子力学
数学
作者
Constanze Hofstoetter,Manuel Gil,Kynan Eng,Giacomo Indiveri,Matti Mintz,Jörg Krämer,Paul F. M. J. Verschure
摘要
We present a biophysically constrained cerebellar model of classical conditioning, implemented using a neuromorphic analog VLSI (aVLSI) chip. Like its biological counterpart, our cerebellar model is able to control adaptive behavior by predicting the precise timing of events. Here we describe the functionality of the chip and present its learning performance, as evaluated in simulated conditioning experiments at the circuit level and in behavioral experiments using a mobile robot. We show that this aVLSI model supports the acquisition and extinction of adaptively timed conditioned responses under real-world conditions with ultra-low power consumption.
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