An analog memory circuit for spiking silicon neurons
Neural Computation
Biologically-Inspired On-Chip Learning in Pulsed Neural Networks
Analog Integrated Circuits and Signal Processing - Special issue on Learning on Silicon
Antidromic Spikes Drive Hebbian Learning in an Artificial Dendritic Tree
Analog Integrated Circuits and Signal Processing - Special issue on Learning on Silicon
Neuromorphic Synapses for Artificial Dendrites
Analog Integrated Circuits and Signal Processing
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The use of switched capacitors as wide-range, programmable resistive elements in spatially extensive artificial dendritic trees (ADT's) is described. We show that silicon neuro-morphs with ADT's can produce impulse responses that last millions of times longer than the initiating impulse and that dynamical responses are tunable in both shape and duration over a wide range. The switched-capacitor resistors forming a dendritic tree are shown indirectly to have a useful programmable resistance range between 500 KΩ and 1000 GΩ. Experimental results are presented that show variable impulse response functions, tunable frequency selectivity, and rate-invariance of spatiotemporal pattern responses