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Compressive Sampling and Lossy Compression
IEEE Signal Processing Magazine, 2008Recent results in compressive sampling have shown that sparse signals can be recovered from a small number of random measurements. This property raises the question of whether random measurements can provide an efficient representation of sparse signals in an information-theoretic sense.
V.K. Goyal, A.K. Fletcher, S. Rangan
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Reweighted Compressive Sampling for image compression
2009 Picture Coding Symposium, 2009Compressive Sampling (CS), is an emerging theory which points us a promising direction of designing novel efficient data compression techniques. However, the conventional CS adopts a non-discriminated sampling scheme which usually gives poor performance on realistic complex signals.
null Yi Yang +4 more
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Node Scheduling and Compressed Sampling for Event Reporting in WSNs
IEEE Transactions on Network Science and Engineering, 2019This work focuses on developing a node scheduling algorithm for detecting events in a sensor field such that few random samples from a set of the active sensor nodes are transmitted to the cluster head and are further used for almost complete ...
V. Singh, Manish Kumar, S. Verma
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Compressive covariance sampling
2013 Information Theory and Applications Workshop (ITA), 2013Most research efforts in the field of compressed sensing have been pointed towards analyzing sampling and reconstruction techniques for sparse signals, where sampling rates below the Nyquist rate can be reached. When only second-order statistics or, equivalently, covariance information is of interest, perfect signal reconstruction is not required and ...
D. Romero, G. Leus
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Compressive sampling experiments
2014 6th European Embedded Design in Education and Research Conference (EDERC), 2014Compressive sampling theory describes methods to reconstruct signals sampled at sub-Nyquist rates. The theory assumes that the signals are sparse in the frequency domain or in the time domain and requires a random sampling process. This paper describes compressive sampling experiments using a 6 Msps ADC (THS1206) and a C6000 DSP.
Carsten Roppel, Martin Danz
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Compressive Sampling for Signal Classification
2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 2006Compressive sampling (CS), also called compressed sensing, entails making observations of an unknown signal by projecting it onto random vectors. Recent theoretical results show that if the signal is sparse (or nearly sparse) in some basis, then with high probability such observations essentially encode the salient information in the signal.
Haupt, J. +4 more
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Adaptive sampling for compressed sensing based image compression
2014 IEEE International Conference on Multimedia and Expo (ICME), 2014A jointly-reweighted block-based compressed sensing scheme.A generic measurement allocation algorithm to assign CS-measurements.Statistical parameters as allocation factors.Two solutions to implement the adaptive measurement allocation.Remarkable quality improvement over the traditional reweighted BCS scheme. The compressed sensing (CS) theory has been
Zhu, Shuyuan +2 more
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Compressive sampling hardware reconstruction
Proceedings of 2010 IEEE International Symposium on Circuits and Systems, 2010Compressive Sampling reconstruction techniques require computationally intensive algorithms, often using L1 optimization to reconstruct a signal that was originally sampled at a sub-Nyquist rate. In this work we present a VLSI implementation of a computationally efficient algorithm named Orthogonal Matching Pursuit. We further optimize the algorithm to
Avi Septimus, Raphael Steinberg
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Sampled speech compression system
The Journal of the Acoustical Society of America, 1985A sampled speech compression and expansion system, for two-dimensional prssing of speech or other type of audio signal, comprises transmit/encode apparatus and receive/decode apparatus. The transmit/encode apparatus comprises a low-pass filter, adapted to receive an input signal, for passing through low-frequency analog signals.
James M. Alsup, Harper J. Whitehouse
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Wideband Photonic Compressive Sampling
Optical Fiber Communication Conference, 2012We discuss the potential benefits of combining the high speeds, broad modulation bandwidths and precision timing of photonic sampling techniques with recent advances in the theory and algorithms of compressive sampling.
Thomas R. Clark +5 more
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