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An Auto-Scaling Wide Dynamic Range Current to Frequency Converter for Real-Time Monitoring of Signals in Neuromorphic Systems


Qiao, Ning; Indiveri, Giacomo (2016). An Auto-Scaling Wide Dynamic Range Current to Frequency Converter for Real-Time Monitoring of Signals in Neuromorphic Systems. In: Biomedical Circuits and Systems Conference (BioCAS), 2016, Shanghai, 17 October 2016 - 19 October 2016.

Abstract

Neuromorphic systems typically employ current-mode circuits that model neural dynamics and produce output currents that range from few pico-Amperes to hundreds of micro-Amperes. On-line real-time monitoring of the signals produced by these circuits is crucial, for prototyping and debugging purposes, as well as for analyzing and understanding the network dynamics and computational properties. To this end, we propose a compact on-chip auto-scaling Current to Frequency Converter (CFC) for real-time monitoring of analog currents in mixed-signal/analog neuromorphic electronic systems. The proposed CFC is a self-timed asynchronous circuit that has a wide dynamic input range of up to 6 decades, ranging from pico-Amps to micro-Amps, with high current measurement sensitivity. To produce a linear output frequency response, while properly covering the wide dynamic input range, the circuit automatically detects the scale of the input current and adjusts the scale of its output firing rate accordingly. Here we describe the proposed circuit and present experimental results measured from multiple instances of the circuit, implemented using a standard 180 nm CMOS process, and interfaced to silicon neuron and synapse circuits for real-time current monitoring. We demonstrate how the circuit is suitable for measuring neural dynamics by showing the converted response properties of the chip silicon neurons and synapses as they are stimulated by input spikes.

Abstract

Neuromorphic systems typically employ current-mode circuits that model neural dynamics and produce output currents that range from few pico-Amperes to hundreds of micro-Amperes. On-line real-time monitoring of the signals produced by these circuits is crucial, for prototyping and debugging purposes, as well as for analyzing and understanding the network dynamics and computational properties. To this end, we propose a compact on-chip auto-scaling Current to Frequency Converter (CFC) for real-time monitoring of analog currents in mixed-signal/analog neuromorphic electronic systems. The proposed CFC is a self-timed asynchronous circuit that has a wide dynamic input range of up to 6 decades, ranging from pico-Amps to micro-Amps, with high current measurement sensitivity. To produce a linear output frequency response, while properly covering the wide dynamic input range, the circuit automatically detects the scale of the input current and adjusts the scale of its output firing rate accordingly. Here we describe the proposed circuit and present experimental results measured from multiple instances of the circuit, implemented using a standard 180 nm CMOS process, and interfaced to silicon neuron and synapse circuits for real-time current monitoring. We demonstrate how the circuit is suitable for measuring neural dynamics by showing the converted response properties of the chip silicon neurons and synapses as they are stimulated by input spikes.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Event End Date:19 October 2016
Deposited On:23 Feb 2018 10:03
Last Modified:31 Jul 2018 05:12
Publisher:Biomedical Circuits and Systems Conference (BioCAS), 2016 IEEE
Series Name:Biomedical Circuits and Systems (BIOCAS) 2016
OA Status:Closed
Free access at:Official URL. An embargo period may apply.
Publisher DOI:https://doi.org/10.1109/BioCAS.2016.7833756
Official URL:http://ncs.ethz.ch/pubs/pdf/QiaoIndiveri16b.pdf

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