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Coil sensitivity encoding for fast MRI. In:

by Klaas P Pruessmann , Markus Weiger , Markus B Scheidegger , Peter Boesiger - Proceedings of the ISMRM 6th Annual Meeting, , 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
Abstract - Cited by 193 (3 self) - Add to MetaCart
configurations and k-space sampling patterns. Special attention is given to the currently most practical case, namely, sampling a common Cartesian grid with reduced density. For this case the feasibility of the proposed methods was verified both in vitro and in vivo. Scan time was reduced to one-half using a two

Voxel-Based Motion Bounding and Workspace Estimation for Robotic Manipulators

by Peter Anderson-sprecher, Reid Simmons
"... Abstract — Identification of regions in space that a robotic manipulator can reach in a given amount of time is important for many applications, such as safety monitoring of industrial manipulators and trajectory and task planning. However, due to the high-dimensional configuration space of many rob ..."
Abstract - Cited by 4 (2 self) - Add to MetaCart
Abstract — Identification of regions in space that a robotic manipulator can reach in a given amount of time is important for many applications, such as safety monitoring of industrial manipulators and trajectory and task planning. However, due to the high-dimensional configuration space of many

1Space-Time Adaptive Processing and Motion Parameter Estimation in Multi-Static Passive Radar Using Sparse Bayesian Learning

by Qisong Wu, Yimin D. Zhang, Senior Member, Moeness G. Amin, Braham Himed
"... Abstract—Conventional space-time adaptive processing suffers from the requirement of a large number of secondary samples. In this paper, a novel method is proposed to accurately estimate the clutter covariance matrix based on a small number of secondary samples by exploiting the common clutter suppo ..."
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support across nearby range cells in the angle-Doppler domain. By taking advantage of the intrinsic sparsity of the clutter in the angle-Doppler domain, the recently developed sparse Bayesian learning tech-nique is employed for high-resolution clutter profile estimation. The proposed method does

CONDENSATION-Conditional Density Propagation for Visual Tracking

by Michael , Andrew Blake , 1998
"... Abstract. The problem of tracking curves in dense visual clutter is challenging. Kalman filtering is inadequate because it is based on Gaussian densities which, being unimodal, cannot represent simultaneous alternative hypotheses. The Condensation algorithm uses "factored sampling", previ ..."
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whether this assumption is justified. The observation density (15) can be computed via a discrete approximation, the simplest being: where s m = m/M. This is simply the product of one-dimensional densities (14) with σ = √ r M, evaluated independently along M curve normals as in Applying the CONDENSATION

CORRECTING FOR PRECIPITATION EFFECTS IN SATELLITE-BASED PASSIVE MICROWAVE TROPICAL CYCLONE INTENSITY ESTIMATES

by Capt Wacker Robert S, Robert S. Wacker , 2005
"... Public reporting burden for this collection of Information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments ..."
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Public reporting burden for this collection of Information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send

1The Cramér–Rao Bound for Sparse Estimation

by Zvika Ben-haim, Student Member, Yonina C. Eldar, Senior Member
"... The goal of this paper is to characterize the best achievable performance for the problem of estimating an unknown parameter having a sparse representation. Specifically, we consider the setting in which a sparsely representable deterministic parameter vector is to be estimated from measurements cor ..."
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with knowledge of the support set, for almost all feasible parameter values. Consequently, in the unbiased case, our bound is identical to the MSE of the oracle estimator. Combined with the fact that the CRB is achieved at high signal-to-noise ratios by the maximum likelihood technique, our result provides a new

New developments in SOLAR2000 for space research and operations

by W Kent Tobiska , S Dave Bouwer - Adv. Space Res , 2006
"... Abstract The SOLAR2000 (S2K) project provides solar spectral irradiances and integrated solar irradiance proxies for space researchers as well as ground-and space-based operational users. The S2K model currently represents empirical solar irradiances and integrated irradiance proxies covering the s ..."
Abstract - Cited by 6 (2 self) - Add to MetaCart
, and forecast irradiances and proxies, including in high time resolution, for ground-and space-based operations; these fee-based applications are available to operational users on any platform through an IDL VM GUI application (S2K PG: daily values), server access (S2K OP: daily plus high time resolution

Scenario Generation and Reduction for Long-term and Short-term Power System Generation Planning under Uncertainties

by Yonghan Feng, James D. Mccalley, William Q. Meeker, Jo Min, Lizhi Wang
"... ii ..."
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Abstract not found

IEEE TRANSACTIONS ON SIGNAL PROCESSING 1 Hidden Relationships: Bayesian Estimation with Partial Knowledge

by Tomer Michaeli, Yonina C. Eldar, Senior Member
"... Abstract—We address the problem of Bayesian estimation where the statistical relation between the signal and measure-ments is only partially known. We propose modeling partial Bayesian knowledge by using an auxiliary random vector called instrument. The statistical relations between the instrument a ..."
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Abstract—We address the problem of Bayesian estimation where the statistical relation between the signal and measure-ments is only partially known. We propose modeling partial Bayesian knowledge by using an auxiliary random vector called instrument. The statistical relations between the instrument

;D'4BEBCE ( BE Generation of a Buoyancy-Driven Coastal Current by an Antarctic Polynya

by Alexander V. Wilchinsky, Daniel L. Feltham , 2007
"... Descent and spreading of high salinity water generated by salt rejection during sea ice formation in an Antarctic coastal polynya is studied using a hydrostatic, primitive equation three-dimensional ocean model called the Proudman Oceanographic Laboratory Coastal Ocean Modeling System (POLCOMS). The ..."
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Descent and spreading of high salinity water generated by salt rejection during sea ice formation in an Antarctic coastal polynya is studied using a hydrostatic, primitive equation three-dimensional ocean model called the Proudman Oceanographic Laboratory Coastal Ocean Modeling System (POLCOMS
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