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Author:
Zheng, Lirong  Leene, Lieuwe B.  Liu, Yan  Constandinou, Timothy G.  


Journal:
2014 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS)


Issue Date:
2014


Abstract(summary):

This paper presents a novel method and circuit for feature-driven data acquisition in single neuron recording. By dynamically adjusting the phase of the sampling clock in a Successive Approximation Register (SAR) Analogue to Digital Converter (ADC), the samples can be maximally aligned to the spike extrema (peaks). This is achieved by using spike detection to switch from a 'coarse' to 'fine' sampling clock, and triggering a peak-search algorithm to determine the offset between the peak occurrence and the coarse clock. Subsequent samples are then aligned to the peak by shifting the coarse clock by the measured offset. This adaptive sampling scheme thus allows for improved temporal precision on features of interest (i.e. peaks) whilst maintaining a coarse effective sampling rate, also minimising power consumption. The proposed method reduces the output data bandwidth by approximately 70% in comparison to a fixed-sampling rate data converter that would achieve similar precision in peak alignment. The circuit implementation achieves 9-bit resolution with a 93 fJ/conversion-step energy efficiency in a standard 0.35 mu m CMOS technology.


Page:
2385---2388


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