Opportunistic Sampling by Level-Crossing

This dissertation addresses an alternative sampling method called level-crossing (LC). In recent years LC has emerged as an alternative to the traditional Nyquist-Shannon based sampling. While the conventional approach is an ideal enabler of reliable and perfect signal reconstruction, it is not always economical and efficient. LC is a threshold-based sampling that is particularly suitable for processing bursty signals, which exist in a diverse range of settings. The motivations for this work are twofold: one is to address signal reconstruction outside of the conventional paradigm, and the other is to address compression in data processing. This work makes the following contributions: 1. consistent reconstruction algorithm via LC for a general class of signals, 2. perfect reconstruction algorithm via LC for signals of finite rate of innovation, 3. a universal sequential algorithm for the placement of reference levels that is competitive with the best static scheme known a priori, and 4. a numerical index that measures signal sparseness which is used to analytically show the relationship between rate of transmission and signal characteristics. The framework established in this work aims to capture the full potential of LC. Insights gained from the analytical work will contribute to the establishment of new data acquisition protocols and provide references for hardware implementations of LC ADCs. ii

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical and Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2012

Author dc:creator

• Guan, Karen

Contributors dc:contributor

• Singer, Andrew C.
• Chiu, Yun
• Do, Minh N.
• Shanbhag, Naresh R.

• level-crossing
• sampling
• bursty
• consistent signal reconstruction
• data compression
• finite rate of innovation
• universal sequential
• Analog-to-Digital Converters (ADCs)

Statement dc:rights

• Copyright 2012 Karen Guan

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/30884

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/30884