Prof. Richard G. Baraniuk
at Rice Univ
SPIE Involvement:
Author | Instructor
Publications (40)

Proceedings Article | 8 June 2012
Proc. SPIE. 8365, Compressive Sensing
KEYWORDS: Long wavelength infrared, Digital micromirror devices, Sensors, Target detection, Mirrors, Signal to noise ratio, Fabry–Perot interferometers, Imaging systems, Compressed sensing, Cameras

Proceedings Article | 27 September 2007
Proc. SPIE. 6701, Wavelets XII
KEYWORDS: Associative arrays, Compressed sensing, Quantization, Feedback loops, Analog electronics, Sensing systems, Linear filtering, Computing systems, Digital filtering, Optimization (mathematics)

Proceedings Article | 27 September 2007
Proc. SPIE. 6701, Wavelets XII
KEYWORDS: Fourier transforms, Phase retrieval, Signal processing, Diffraction, Terahertz radiation, Compressed sensing, Wavelets, Detection theory, Chemical elements, Algorithm development

Proceedings Article | 28 February 2007
Proc. SPIE. 6498, Computational Imaging V
KEYWORDS: Image classification, Image compression, Image filtering, Cameras, Optical filters, Compressed sensing, Target recognition, Digital micromirror devices, Matrices, Error analysis

Proceedings Article | 2 February 2006
Proc. SPIE. 6065, Computational Imaging IV
KEYWORDS: Wavelets, Digital micromirror devices, Cameras, Mirrors, Imaging systems, Reconstruction algorithms, Image compression, Photodiodes, Compressive imaging, Sensors

Showing 5 of 40 publications
Conference Committee Involvement (9)
Sensing and Analysis Technologies for Biomedical and Cognitive Applications 2016
17 April 2016 | Baltimore, Maryland, United States
Independent Component Analyses, Compressive Sampling, Large Data Analyses (LDA), Neural Networks, Biosystems, and Nanoengineering XIII
23 April 2015 | Baltimore, Maryland, United States
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XII
7 May 2014 | Baltimore, Maryland, United States
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI
1 May 2013 | Baltimore, Maryland, United States
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering X
25 April 2012 | Baltimore, Maryland, United States
Showing 5 of 9 Conference Committees
Course Instructor
SC902: Compressive Sensing: Theory and Applications
Sensors and signal processing hardware and algorithms are under increasing pressure to accommodate ever larger and higher-dimensional data sets; ever faster capture, sampling, and processing rates; ever lower power consumption; communication over ever more difficult channels; and radically new sensing modalities. This four-hour course presents the fundamental theory and selected applications of Compressive Sensing, a new approach to data acquisition in which analog signals are digitized for processing not via uniform sampling but via inner products with random test functions. Unlike Nyquist-rate sampling, which completely describes a signal by exploiting its bandlimitedness, Compressive Sensing reduces the number of measurements required to completely describe a signal by exploiting its compressibility. The implications are promising for many applications and enable the design of new kinds of analog-to-digital converters, imaging systems and cameras, and radar systems, among others.
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