一种专用于神经记录脑植入物的10- b330nw三阶预测SAR ADC

Mohsen Namavar, R. Lotfi, A. M. Sodagar
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引用次数: 0

摘要

本文报道了一种预测模数转换器(ADC)。所提出的ADC采用线性预测滤波器,根据先前数字代码的值对当前样本进行预测。这导致转换器的平均位周期显著降低。这项工作表明,这种想法对于生物信号(例如,皮质内神经信号)的数字化更为有效。与文献中可用的其他类似技术相比,所提出的预测ADC在小信噪比下显着更成功。与传统结构和LSB-first结构相比,该算法可将转换器的平均比特周期分别降低48%和37%。该10位预测ADC采用90纳米标准CMOS技术进行设计和后期布局仿真,工作速度为200ks /s,电源电压为0.4 V,功耗为330 nW。该电路的核心面积为0.025 mm2, ENOB为9.42位,品质因数为2.4 fJ/conv。-step, SFDR为65.8 dB。电路的DNL和INL分别在0.45 LSB和0.56 LSB以内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A 10-b 330nW Third-Order Predictive SAR ADC Dedicated to Neural Recording Brain Implants
This paper reports on a predictive analog-todigital converter (ADC). The proposed ADC employs a linear predictive filter to prepare a prediction for the current sample based on the values of the previous digital codes. This leads to significant reduction in the mean bit cycle of the converter. It is shown in this work that this idea is significantly more effective for the digitization of biological signals (e.g., intra-cortical neural signals). Compared with other similar techniques available in the literature, the proposed predictive ADC is significantly more successful for small signal-to-noise ratios. The proposed algorithm results in 48% and 37% reduction in the converter’s mean bit cycle compared with the conventional and LSB-first structures, respectively. Designed and post-layout simulated in a 90-nm standard CMOS technology and operated at 200 kS/s with a supply voltage of 0.4 V, the 10-bit predictive ADC consumes 330 nW. The circuit occupies a core area of 0.025 mm2, achieves an ENOB of 9.42 bits, a figure-of-merit of 2.4 fJ/conv.-step, and an SFDR of 65.8 dB. The DNL and INL of the circuit are within 0.45 LSB and 0.56 LSB, respectively.
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