Results 1  10
of
486
Nonlinear inverse scale space methods for image restoration
 Communications in Mathematical Sciences
, 2005
"... Abstract. In this paper we generalize the iterated refinement method, introduced by the authors in [8], to a timecontinuous inverse scalespace formulation. The iterated refinement procedure yields a sequence of convex variational problems, evolving toward the noisy image. The inverse scale space m ..."
Abstract

Cited by 65 (18 self)
 Add to MetaCart
Abstract. In this paper we generalize the iterated refinement method, introduced by the authors in [8], to a timecontinuous inverse scalespace formulation. The iterated refinement procedure yields a sequence of convex variational problems, evolving toward the noisy image. The inverse scale space
Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems
 IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
, 2007
"... Many problems in signal processing and statistical inference involve finding sparse solutions to underdetermined, or illconditioned, linear systems of equations. A standard approach consists in minimizing an objective function which includes a quadratic (squared ℓ2) error term combined with a spa ..."
Abstract

Cited by 539 (17 self)
 Add to MetaCart
of applications, often being significantly faster (in terms of computation time) than competing methods. Although the performance of GP methods tends to degrade as the regularization term is deemphasized, we show how they can be embedded in a continuation scheme to recover their efficient practical performance.
Improved Localization of Cortical Activity by Combining EEG and MEG with MRI Cortical Surface Reconstruction: A Linear Approach
 J. Cogn. Neurosci
, 1993
"... We describe a comprehensive linear approach to the prob lem of imaging brain activity with high temporal as well as spatial resolution based on combining EEG and MEG data with anatomical constraints derived from MRI images. The "inverse problem" of estimating the distribution of dipole st ..."
Abstract

Cited by 263 (19 self)
 Add to MetaCart
is recursively fiood4illed ,o determine the topology of the gray.white matter border, and (3) the resulting continuous surface is refinc by relaxing it against the original 3D grayscale image using a deformable template method, which is also used to computationally flatten the cortex for k'asier vic
Coil sensitivity encoding for fast MRI. In:
 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
complementary to Fourier preparation by linear field gradients. Thus, by using multiple receiver coils in parallel scan time in Fourier imaging can be considerably reduced. The problem of image reconstruction from sensitivity encoded data is formulated in a general fashion and solved for arbitrary coil
The Inverse Source Problem of Electromagnetics: Linear Inversion Formulation and Minimum Energy Solution
"... the mode occurs at �™�� � aSGHz. Fig. 2(a) ( � aIHGHz) and Fig. 2(b) ( � aPGHz), show the radiated field for frequencies above and below the cutoff, respectively. In both cases, the line integration (continuous line) and the surface integrations (dots) lead to identical results in the limit of the ..."
Abstract
 Add to MetaCart
the mode occurs at �™�� � aSGHz. Fig. 2(a) ( � aIHGHz) and Fig. 2(b) ( � aPGHz), show the radiated field for frequencies above and below the cutoff, respectively. In both cases, the line integration (continuous line) and the surface integrations (dots) lead to identical results in the limit
Correlated continuous time random walks
"... Abstract. Continuous time random walks impose a random waiting time before each particle jump. Scaling limits of heavy tailed continuous time random walks are governed by fractional evolution equations. Spacefractional derivatives describe heavy tailed jumps, and the timefractional version codes h ..."
Abstract

Cited by 10 (4 self)
 Add to MetaCart
Abstract. Continuous time random walks impose a random waiting time before each particle jump. Scaling limits of heavy tailed continuous time random walks are governed by fractional evolution equations. Spacefractional derivatives describe heavy tailed jumps, and the timefractional version codes
Space, Scale, and Scaling in Entropy Maximizing
"... Entropy measures were first introduced into geographical analysis during a period when the concept of human systems in equilibrium was in its ascendancy. In particular, entropy maximizing, in direct analogy with equilibrium statistical mechanics, provides a powerful framework in which to generate l ..."
Abstract
 Add to MetaCart
location and interaction models. This was introduced and popularized by Wilson, and it led to many different extensions that elaborate the framework rather than extend it to different kinds of models. I review two such extensions here: how space can be introduced into the formulation through defining a
Parallel Multiscale GaussNewtonKrylov Methods For Inverse Wave Propagation
, 2002
"... One of the outstanding challenges of computational science and engineering is largescale nonlinear parameter estimation of systems governed by partial differential equations. These are known as inverse problems,in contradistinction to the forward problems that usually characterize largescale simu ..."
Abstract

Cited by 51 (18 self)
 Add to MetaCart
simulation. Inverse problems are significantly more difficult to solve than forward problems, due to illposedness, large dense illconditioned operators, multiple minima, spacetime coupling, and the need to solve the forward problem repeatedly. We present a parallel algorithm for inverse problems governed
Terrain aware inversion of predictive models for high performance
"... The capacity to predict motion adequately over the time scale of a few seconds is fundamental to autonomous mobility. Model predictive optimal control is a general formalism within which most historical approaches can be cast as special cases. Applications continue to grow in ambition to seek higher ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
The capacity to predict motion adequately over the time scale of a few seconds is fundamental to autonomous mobility. Model predictive optimal control is a general formalism within which most historical approaches can be cast as special cases. Applications continue to grow in ambition to seek
Interval Estimation of Bounded Variable Means via Inverse Sampling ∗
, 2008
"... In this paper, we develop interval estimation methods for means of bounded random variables based on a sequential procedure such that the sampling is continued until the sample sum is no less than a prescribed threshold. 1 Inverse Sampling It is a ubiquitous problem to estimate the means of bounded ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
In this paper, we develop interval estimation methods for means of bounded random variables based on a sequential procedure such that the sampling is continued until the sample sum is no less than a prescribed threshold. 1 Inverse Sampling It is a ubiquitous problem to estimate the means of bounded
Results 1  10
of
486