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Results 1 - 8 of 8

port Vector Machines, Kernel Fisher Discriminant analysis

by Sebastian Mika, Koji Tsuda
"... Abstract | This review provides an introduction to Sup- ..."
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Abstract | This review provides an introduction to Sup-

2 NONMONOTONE BARZILAI-BORWEIN GRADIENT ALGORITHM FOR ℓ1-REGULARIZED NONSMOOTH MINIMIZATION IN COMPRESSIVE SENSING

by unknown authors
"... ar ..."
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JEAN-LUC GENNISSON

by Universite Paris, Vi Pierre, Et Marie Curie, Espci Paristech, Habilitation A Diriger Des, Dr. Damien, Pr. Michel, Dr. Mickaël, Tanter Examinateur, Jean-luc Gennisson, H. D. R. Université, Paris Vi
"... RECHERCHES Elastographie par ondes de cisaillement ..."
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RECHERCHES Elastographie par ondes de cisaillement

IEEE TRANSACTIONS ON INFORMATION THEORY (SUBMITTED) 1 Noisy Matrix Completion under Sparse Factor Models

by Akshay Soni, Swayambhoo Jain, Jarvis Haupt, Stefano Gonella
"... ar ..."
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AND MATHEMATICAL ENGINEERING

by Madeleine Udell, Professor Lester Mackey , 2015
"... ii ..."
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Subspace Communication

by Josep Font-segura, Prof Gregori , 2014
"... We are surrounded by electronic devices that take advantage of wireless technologies, from our computer mice, which require little amounts of information, to our cellphones, which demand increasingly higher data rates. Until today, the coexistence of such a variety of services has been guaranteed by ..."
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by a fixed assignment of spectrum resources by regulatory agencies. This has resulted into a blind alley, as current wireless spectrum has become an expensive and a scarce resource. However, recent measurements in dense areas paint a very different picture: there is an actual underutilization

RICE UNIVERSITY Regime Change: Sampling Rate vs. Bit-Depth in Compressive Sensing

by Jason Noah Laska , 2011
"... The compressive sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by exploiting inherent structure in natural and man-made signals. It has been demon-strated that structured signals can be acquired with just a small number of linear measurements, on the order of t ..."
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The compressive sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by exploiting inherent structure in natural and man-made signals. It has been demon-strated that structured signals can be acquired with just a small number of linear measurements, on the order of the signal complexity. In practice, this enables lower sampling rates that can be more easily achieved by current hardware designs. The primary bottleneck that limits ADC sam-pling rates is quantization, i.e., higher bit-depths impose lower sampling rates. Thus, the decreased sampling rates of CS ADCs accommodate the otherwise limiting quantizer of conventional ADCs. In this thesis, we consider a different approach to CS ADC by shifting towards lower quantizer bit-depths rather than lower sampling rates. We explore the extreme case where each measurement is quantized to just one bit, representing its sign. We develop a new theoretical framework to analyze this extreme case and develop new algorithms for signal reconstruction from such coarsely quantized measurements. The 1-bit CS framework leads us to scenarios where it may be more appropriate to reduce bit-depth instead of sampling rate. We find that there exist two distinct regimes of operation that correspond to high/low signal-to-noise ratio (SNR). In the measurement

1Sub-Nyquist Sampling: Bridging Theory and Practice

by Moshe Mishali, Yonina C. Eldar
"... [ A review of past and recent strategies for sub-Nyquist sampling] Signal processing methods have changed substantially over the last several decades. In modern applications, an increasing number of functions is being pushed forward to sophisticated software algorithms, leaving only delicate finely- ..."
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[ A review of past and recent strategies for sub-Nyquist sampling] Signal processing methods have changed substantially over the last several decades. In modern applications, an increasing number of functions is being pushed forward to sophisticated software algorithms, leaving only delicate finely
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