2026-09-20T01:14:33Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/353002022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Rahul Sarpeshkar.
Yang, Heemin Yi, 1976-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2007-01-10T15:36:57Z
2007-01-10T15:36:57Z
2006
2006
http://hdl.handle.net/1721.1/35300
74907051
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (leaves 123-129).
Dual-slope converters use time to perform analog-to-digital conversion but require 2N+1 clock cycles to achieve N bits of precision. We describe a novel algorithm that also uses time to perform analog-to-digital conversion but requires 5N clock cycles to achieve N bits of precision via a successive sub-ranging technique. The algorithm requires one asynchronous comparator, two capacitors, one current source, and a state machine. Amplification of two is achieved without the use of an explicit amplifier by simply doing things twice in time. The use of alternating Voltage-to-Time and Time-to-Voltage conversions provides natural error cancellation of comparator offset and delay, 1/f noise, and switching charge-injection. The use of few components and an effcient mechanism for amplification and error cancellation allow for energy-effcient operation: In a 0.35 [mu]m implementation, we were able to achieve 12 bits of DNL limited precision or 11 bits of thermal noise-limited precision at a sampling frequency of 31.25kHz with 75 [mu] W of total analog and digital power consumption. These numbers yield a thermal noise-limited energy-efficiency of 1.17pJ per quantization level making it one of the most energy-effcient converters to date in the 10 to 12 bit precision range.
(cont.) This converter could be useful in low-power hearing aids after analog gain control has been performed on a microphone front-end. An 8 bit audio version of our converter in a 0.18 [mu] m process consumes 960nW and yields an energy-efficiency of 0.12pJ per quantization level, perhaps the lowest ever reported. This converter may be useful in biomedical and sensor-network applications where energy-efficiency is paramount. Our algorithm has inherent advantages in time-to-digital conversion. It can be generalized to easily digitize power-law functions of its input, and it can be used in an interleaved architecture if higher speed is desired.
by Heemin Yi Yang.
Ph.D.
129 leaves
10627030 bytes
10636336 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
A time-based energy-efficient analog-to-digital converter
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<Abstract>Dual-slope converters use time to perform analog-to-digital conversion but require 2N+1 clock cycles to achieve N bits of precision. We describe a novel algorithm that also uses time to perform analog-to-digital conversion but requires 5N clock cycles to achieve N bits of precision via a successive sub-ranging technique. The algorithm requires one asynchronous comparator, two capacitors, one current source, and a state machine. Amplification of two is achieved without the use of an explicit amplifier by simply doing things twice in time. The use of alternating Voltage-to-Time and Time-to-Voltage conversions provides natural error cancellation of comparator offset and delay, 1/f noise, and switching charge-injection. The use of few components and an effcient mechanism for amplification and error cancellation allow for energy-effcient operation: In a 0.35 [mu]m implementation, we were able to achieve 12 bits of DNL limited precision or 11 bits of thermal noise-limited precision at a sampling frequency of 31.25kHz with 75 [mu] W of total analog and digital power consumption. These numbers yield a thermal noise-limited energy-efficiency of 1.17pJ per quantization level making it one of the most energy-effcient converters to date in the 10 to 12 bit precision range.</Abstract>
<Abstract>(cont.) This converter could be useful in low-power hearing aids after analog gain control has been performed on a microphone front-end. An 8 bit audio version of our converter in a 0.18 [mu] m process consumes 960nW and yields an energy-efficiency of 0.12pJ per quantization level, perhaps the lowest ever reported. This converter may be useful in biomedical and sensor-network applications where energy-efficiency is paramount. Our algorithm has inherent advantages in time-to-digital conversion. It can be generalized to easily digitize power-law functions of its input, and it can be used in an interleaved architecture if higher speed is desired.</Abstract>
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