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A Time-Mode Translinear Principle an...

ProQuest Information and Learning Co.

A Time-Mode Translinear Principle and its Application to Analog Hardware for Pattern Recognition and Machine Learning.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	A Time-Mode Translinear Principle and its Application to Analog Hardware for Pattern Recognition and Machine Learning./
作者:	D'Angelo, Robert.
面頁冊數:	1 online resource (182 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
標題:	Electrical engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9780355345766

A Time-Mode Translinear Principle and its Application to Analog Hardware for Pattern Recognition and Machine Learning.
D'Angelo, Robert.

A Time-Mode Translinear Principle and its Application to Analog Hardware for Pattern Recognition and Machine Learning. - 1 online resource (182 pages)

Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.

Thesis (Ph.D.)--Tufts University, 2017.

Includes bibliographical references

This work proposes a time-mode translinear principle as a process and voltage scalable technique for nonlinear analog computation that is independent of transistor physics. The principle utilizes the exponential relationships between a variable of interest and time in a first order system to realize nonlinear analog computation. A voltage-mode analog multiplier using this principle is introduced. The circuit is then reformulated as a purely time-mode multiplier to reduce the power consumption of the circuit itself as well as the analog-to-digital interface. Next, an asynchronous, differential implementation is proposed for further reducing the power consumption and boosting the dynamic range. Other useful linear and nonlinear circuit functions are also explored. Finally, the design of an application system, an analog neuromorphic image saliency algorithm, is described to motivate the new technique for pattern recognition hardware.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355345766Subjects--Topical Terms:

596380
Electrical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

A Time-Mode Translinear Principle and its Application to Analog Hardware for Pattern Recognition and Machine Learning.
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245 1 2 $a A Time-Mode Translinear Principle and its Application to Analog Hardware for Pattern Recognition and Machine Learning.
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500 $a Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
500 $a Adviser: Sameer R. Sonkusale.
502 $a Thesis (Ph.D.)--Tufts University, 2017.
504 $a Includes bibliographical references
520 $a This work proposes a time-mode translinear principle as a process and voltage scalable technique for nonlinear analog computation that is independent of transistor physics. The principle utilizes the exponential relationships between a variable of interest and time in a first order system to realize nonlinear analog computation. A voltage-mode analog multiplier using this principle is introduced. The circuit is then reformulated as a purely time-mode multiplier to reduce the power consumption of the circuit itself as well as the analog-to-digital interface. Next, an asynchronous, differential implementation is proposed for further reducing the power consumption and boosting the dynamic range. Other useful linear and nonlinear circuit functions are also explored. Finally, the design of an application system, an analog neuromorphic image saliency algorithm, is described to motivate the new technique for pattern recognition hardware.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Electrical engineering. $3 596380
650 4 $a Computer science. $3 573171
655 7 $a Electronic books. $2 local $3 554714
690 $a 0544
690 $a 0984
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Tufts University. $b Electrical Engineering. $3 1184138
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10623213 $z click for full text (PQDT)

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