Characterizing the firing properties of an adaptive analog VLSI neuron

Ben Dayan Rubin D, Chicca E, Indiveri G (2004)
Biologically Inspired Approaches to Advanced Information Technology 3141: 189-200.

Download
OA
Zeitschriftenaufsatz | Veröffentlicht | Englisch
Volltext vorhanden für diesen Nachweis
Autor
; ;
Abstract / Bemerkung
We describe the response properties of a compact, low power, analog circuit that implements a model of a leaky-Integrate & Fire (I&F) neuron, with spike-frequency adaptation, refractory period and voltage threshold modulation properties. We investigate the statistics of the circuit's output response by modulating its operating parameters, like refractory period and adaptation level and by changing the statistics of the input current. The results show a clear match with theoretical prediction and neurophysiological data in a given range of the parameter space. This analysis defines the chip's parameter working range and predicts its behavior in case of integration into large massively parallel very-large-scale-integration (VLSI) networks.
Erscheinungsjahr
Zeitschriftentitel
Biologically Inspired Approaches to Advanced Information Technology
Band
3141
Seite
189-200
PUB-ID

Zitieren

Ben Dayan Rubin D, Chicca E, Indiveri G. Characterizing the firing properties of an adaptive analog VLSI neuron. Biologically Inspired Approaches to Advanced Information Technology. 2004;3141:189-200.
Ben Dayan Rubin, D., Chicca, E., & Indiveri, G. (2004). Characterizing the firing properties of an adaptive analog VLSI neuron. Biologically Inspired Approaches to Advanced Information Technology, 3141, 189-200. doi:10.1007/978-3-540-27835-1_15
Ben Dayan Rubin, D., Chicca, E., and Indiveri, G. (2004). Characterizing the firing properties of an adaptive analog VLSI neuron. Biologically Inspired Approaches to Advanced Information Technology 3141, 189-200.
Ben Dayan Rubin, D., Chicca, E., & Indiveri, G., 2004. Characterizing the firing properties of an adaptive analog VLSI neuron. Biologically Inspired Approaches to Advanced Information Technology, 3141, p 189-200.
D. Ben Dayan Rubin, E. Chicca, and G. Indiveri, “Characterizing the firing properties of an adaptive analog VLSI neuron”, Biologically Inspired Approaches to Advanced Information Technology, vol. 3141, 2004, pp. 189-200.
Ben Dayan Rubin, D., Chicca, E., Indiveri, G.: Characterizing the firing properties of an adaptive analog VLSI neuron. Biologically Inspired Approaches to Advanced Information Technology. 3141, 189-200 (2004).
Ben Dayan Rubin, D., Chicca, Elisabetta, and Indiveri, G. “Characterizing the firing properties of an adaptive analog VLSI neuron”. Biologically Inspired Approaches to Advanced Information Technology 3141 (2004): 189-200.
Alle Dateien verfügbar unter der/den folgenden Lizenz(en):
Copyright Statement:
This Item is protected by copyright and/or related rights. [...]
Volltext(e)
Access Level
OA Open Access
Zuletzt Hochgeladen
2012-01-09T10:29:21Z