J. Laska

发表

An Architecture for Compressive Imaging

Richard G. Baraniuk, Michael B. Wakin, Shriram Sarvotham, 2006, 2006 International Conference on Image Processing.

Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors

Laurent Jacques, Richard G. Baraniuk, Petros Boufounos, 2011, IEEE Transactions on Information Theory.

Analog-to-Information Conversion via Random Demodulation

S. Kirolos, T. Ragheb, J. Laska, 2006, 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software.

Multiscale Random Projections for Compressive Classification

Richard G. Baraniuk, Michael B. Wakin, Marco F. Duarte, 2007, 2007 IEEE International Conference on Image Processing.

Compressed Sensing for Imaging Applications by Dharmpal Takhar

D. Takhar, D. Mittleman, J. Laska, 2014 .

Compressed Sensing and its Applications in Imaging

Richard G. Baraniuk, Marco F. Duarte, Kevin F. Kelly, 2008 .

A single pixel camera based on compressed sensing

Richard G. Baraniuk, Marco F. Duarte, Kevin F. Kelly, 2006 .

Compressed Sensing for Multispectral and Confocal Microscopy

Richard G. Baraniuk, Marco F. Duarte, Kevin F. Kelly, 2007 .

Realization of Confocal and Hyperspectral Microscopy via Compressive Sensing

Richard G. Baraniuk, Marco F. Duarte, Kevin F. Kelly, 2008 .

The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding vs. Dynamic Range pdf

Richard G. Baraniuk, Mark A. Davenport, John R. Treichler, 2011, ArXiv.

Single-pixel imaging via compressive sampling

Ting Sun, Marco F. Duarte, R.G. Baraniuk, 2008, IEEE Signal Process. Mag..

A new compressive imaging camera architecture using optical-domain compression

Richard G. Baraniuk, Michael B. Wakin, Shriram Sarvotham, 2006, Electronic Imaging.

United States Patent Baraniuk

J. Tropp, J. Laska, Timothy R. DeWitt, 2012 .

A prototype hardware for random demodulation based compressive analog-to-digital conversion

S. Kirolos, T. Ragheb, Y. Massoud, 2008, 2008 51st Midwest Symposium on Circuits and Systems.

DepartmentofElectricalandComputerEngineering,RiceUniversity,Houston,TX DepartmentsofMathematicsandEECS,UniversityofMichigan,AnnArbor,MI

S. Kirolos, T. Ragheb, Y. Massoud, 2022 .

Theory and Implementation of an Analog-to-Information Converter using Random Demodulation

Richard G. Baraniuk, Marco F. Duarte, Yehia Massoud, 2007, 2007 IEEE International Symposium on Circuits and Systems.

Practical Issues in Implementing Analog-to-Information Converters

S. Kirolos, T. Ragheb, J. Laska, 2006, 2006 6th International Workshop on System on Chip for Real Time Applications.

Random Sampling for Analog-to-Information Conversion of Wideband Signals

S. Kirolos, Y. Massoud, R. Baraniuk, 2006, 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software.

The smashed filter for compressive classification and target recognition

Richard G. Baraniuk, Michael B. Wakin, Marco F. Duarte, 2007, Electronic Imaging.

Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals

Justin K. Romberg, Richard G. Baraniuk, Joel A. Tropp, 2009, IEEE Transactions on Information Theory.

Trust, But Verify: Fast and Accurate Signal Recovery From 1-Bit Compressive Measurements

Wotao Yin, Richard G. Baraniuk, Jason N. Laska, 2011, IEEE Transactions on Signal Processing.

The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding versus Dynamic Range

Richard G. Baraniuk, Mark A. Davenport, John R. Treichler, 2011, IEEE Transactions on Signal Processing.

DYNAMIC RANGE AND COMPRESSIVE SENSING ACQUISITION RECEIVERS

Richard G. Baraniuk, Mark A. Davenport, John R. Treichler, 2011 .

The polyphase random demodulator for wideband compressive sensing

Richard G. Baraniuk, Jason N. Laska, John P. Slavinsky, 2011, 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

Democracy in Action: Quantization, Saturation, and Compressive Sensing

Richard G. Baraniuk, Petros T. Boufounos, Mark A. Davenport, 2011 .

Regime Change: Bit-Depth Versus Measurement-Rate in Compressive Sensing

Richard G. Baraniuk, Jason N. Laska, Richard Baraniuk, 2011, IEEE Transactions on Signal Processing.

Compressive sensing for dynamic spectrum access networks: Techniques and tradeoffs

Keith E. Nolan, Thomas W. Rondeau, J. N. Laska, 2011, 2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

Texas Hold 'Em algorithms for distributed compressive sensing

Chinmay Hegde, Richard G. Baraniuk, Marco F. Duarte, 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

A simple proof that random matrices are democratic pdf

Richard G. Baraniuk, Petros Boufounos, Mark A. Davenport, 2009, ArXiv.

Exact signal recovery from sparsely corrupted measurements through the Pursuit of Justice

Richard G. Baraniuk, Mark A. Davenport, Jason N. Laska, 2009, 2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers.

Regime change: sampling rate vs. bit-depth in compressive sensing

Richard G. Baraniuk, Jason N. Laska, Richard Baraniuk, 2011 .

On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion

Richard G. Baraniuk, Anna C. Gilbert, Yehia Massoud, 2008, 2008 IEEE International Symposium on Circuits and Systems.

Compressive imaging for video representation and coding

Richard G. Baraniuk, Michael B. Wakin, Shriram Sarvotham, 2006 .

The compressive multiplexer for multi-channel compressive sensing

Richard G. Baraniuk, Mark A. Davenport, Jason N. Laska, 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).