Minimizing the effect of process mismatch in a neuromorphic system using spike-timing-dependent adaptation.
This paper investigates whether spike-timing-dependent plasticity (STDP) can minimize the effect of mismatch within the context of a depth-from-motion algorithm. To improve noise rejection, this algorithm contains a spike prediction element, whose performance is degraded by analog very large scale integration (VLSI) mismatch. The error between the actual spike arrival time and the prediction is used as the input to an STDP circuit, to improve future predictions. Before STDP adaptation, the error reflects the degree of mismatch within the prediction circuitry. After STDP adaptation, the error indicates to what extent the adaptive circuitry can minimize the effect of transistor mismatch. The circuitry is tested with static and varying prediction times and chip results are presented. The effect of noisy spikes is also investigated. Under all conditions the STDP adaptation is shown to improve performance.
Cameron
Katherine
K
School of Engineering and Electronics, The University of Edinburgh, Edinburgh EH9 3JL, UK. K.Cameron@ed.ac.uk
Murray
Alan
A
D000465:Algorithms; D004581:Electronics; D016571:Neural Networks, Computer; D009473:Neuronal Plasticity; D009474:Neurons / Q000502:physiology; D014173:Transistors, Electronic