An asynchronous ADC with reconfigurable analog pre-processing

Kelly, Brandon M.; Lane, David W. Graham

doi:10.1109/iscas.2016.7527427

Cited by 6 publications

(9 citation statements)

References 9 publications

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“…The well-tuned analog front-end, combined with asynchronous data conversion, allows for highly efficient data extraction. This work is an extension of our earlier work presented in [2], which demonstrated the promise of an asynchronous ADC coupled with analog preprocessing. Here, we provide further circuit details, a discussion on a sampling method that works in conjunction with asynchronous conversion, and additional example applications.…”

Section: Introductionmentioning

confidence: 76%

Reconfigurable Analog Preprocessing for Efficient Asynchronous Analog-to-Digital Conversion

Kelly

DiLello

Graham

2019

JLPEA

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Wearable medical devices, wireless sensor networks, and other energy-constrained sensing devices are often concerned with finding specific data within more-complex signals while maintaining low power consumption. Traditional analog-to-digital converters (ADCs) can capture the sensor information at a high resolution to enable a subsequent digital system to process for the desired data. However, traditional ADCs can be inefficient for applications that only require specific points of data. This work offers an alternative path to lower the energy expenditure in the quantization stage-asynchronous content-dependent sampling. This asynchronous sampling scheme is achieved by pairing a flexible analog front-end with an asynchronous successive-approximation ADC and a time-to-digital converter. The versatility and reprogrammability of this system allows a multitude of event-driven, asynchronous, or even purely data-driven quantization methods to be implemented for a variety of different applications. The system, fabricated in standard 0.5 µm and 0.35 µm processes, is demonstrated along with example applications with voice, EMG, and ECG signals.

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Section: Introductionmentioning

confidence: 76%

Reconfigurable Analog Preprocessing for Efficient Asynchronous Analog-to-Digital Conversion

Kelly

DiLello

Graham

2019

JLPEA

Self Cite

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“…The obvious and most unattractive feature of this method is that it requires computation of the derivative of a signal. However, low-power implementations have been demonstrated in fabricated systems which only attempt to find an accurate zero crossing of the derivative [24,71]. This advantage cannot be understated, as it is know that taking a full and accurate derivative is an extremely costly task [72].…”

Section: Energy-constrained Samplingmentioning

confidence: 99%

“…The only part of the derivative that need be accurate is its zero-crossing. While the derivative could be implemented with any standard derivative circuit [72], we have found that the use of an asymmetric envelope detector [76] works well over a reasonable range of frequencies, such as those required for voice detection [24] or bio-signal monitoring [71].…”

Section: Sampler and Quantizer Implementationmentioning

confidence: 99%

“…Discrete signal monitoring devices such as wireless sensor networks [90], implantable biomedical devices [91], or wearable devices [71] provide extremely useful data and functionality, but must work within very energy-constrained environments. It is easy to only think about the sensors role in the energy budget, but these discretized devices must not only sense the phenomena, they must also quantize it, and often times they must also transmit it.…”

Section: Data Converter Efficiencymentioning

confidence: 99%

“…We can subrange a pFET implementation and an nFET implementation to create a full-scale range comparator by choosing the appropriate implementation based upon the determination of the first bit (Fig. 7.3(b)), as we demonstrated in [71].…”

Section: Comparatormentioning

confidence: 99%

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Data Conversion Within Energy Constrained Environments

Kelly¹

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Within scientific research, engineering, and consumer electronics, there is a multitude of new discrete sensor-interfaced devices. Maintaining high accuracy in signal quantization while staying within the strict power-budget of these devices is a very challenging problem. Traditional paths to solving this problem include researching more energy-efficient digital topologies as well as digital scaling. This work offers an alternative path to lower-energy expenditure in the quantization stage-content-dependent sampling of a signal. Instead of sampling at a constant rate, this work explores techniques which allow sampling based upon features of the signal itself through the use of application-dependent analog processing. This work presents an asynchronous sampling paradigm, based off the use of floating-gate-enabled analog circuitry. The basis of this work is developed through the mathematical models necessary for asynchronous sampling, as well the SPICE-compatible models necessary for simulating floating-gate enabled analog circuitry. These base techniques and circuitry are then extended to systems and applications utilizing novel analog-to-digital converter topologies capable of leveraging the non-constant sampling rates for significant sample and power savings. iii Dedication Marriage is a promise, a potential, made in the hearts of two people who love, which takes a lifetime to fulfill.-Edmund O'Neil Dedicated to Erica and the lifetime we will spend fulfilling that promise. First, thank you to my family for all of the love and support over the years. I'm lucky to have such a large family, and even luckier to feel so close with all of them.

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