LDR | | 02094nam u200397 4500 |
001 | | 000000419688 |
005 | | 20190215163856 |
008 | | 181129s2018 |||||||||||||||||c||eng d |
020 | |
▼a 9780438344426 |
035 | |
▼a (MiAaPQ)AAI10928109 |
035 | |
▼a (MiAaPQ)cornellgrad:11051 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
082 | 0 |
▼a 621.3 |
100 | 1 |
▼a Cao, Yingqiu.
▼0 (orcid)0000-0001-6534-8508. |
245 | 10 |
▼a Variation Resolutions for CMOS Sensing Networks. |
260 | |
▼a [S.l.]:
▼b Cornell University.,
▼c 2018. |
260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
300 | |
▼a 131 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B. |
500 | |
▼a Adviser: Edwin Chihchuan Kan. |
502 | 1 |
▼a Thesis (Ph.D.)--Cornell University, 2018. |
520 | |
▼a Variation and variability have become the main concerns for reliable design methodology in CMOS sensing networks. On one hand, the variation can originate from the sensor tag itself, where the performance can be compromised by the uncontrollable |
520 | |
▼a On the other hand, the sensing variation can originate from the targeted biological sensing signal, which complicates both the sensor system design and the associated signal analysis. We will illustrate a spike-sorting method to reliably classif |
520 | |
▼a Although other variation sources can also affect the sensor system design, our approaches of device compensation based on operational feedback and signal tolerance based on time warping are able to give illustrations for sensor designers to succ |
590 | |
▼a School code: 0058. |
650 | 4 |
▼a Electrical engineering. |
690 | |
▼a 0544 |
710 | 20 |
▼a Cornell University.
▼b Electrical and Computer Engineering. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 80-01B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0058 |
791 | |
▼a Ph.D. |
792 | |
▼a 2018 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000885
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a ***1012033 |