Journal ArticleDOI
Methods of Theoretical Physics. By P.M. Morse and H. Feschbach. 2vols., Pp.xxii, 1978. 120s. each vol. 1953.(McGraw-Hill)
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This article is published in The Mathematical Gazette.The article was published on 1955-02-01. It has received 9185 citations till now.read more
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The random walk's guide to anomalous diffusion: a fractional dynamics approach
Ralf Metzler,Joseph Klafter +1 more
TL;DR: Fractional kinetic equations of the diffusion, diffusion-advection, and Fokker-Planck type are presented as a useful approach for the description of transport dynamics in complex systems which are governed by anomalous diffusion and non-exponential relaxation patterns.
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Snakes, shapes, and gradient vector flow
Chenyang Xu,Jerry L. Prince +1 more
TL;DR: This paper presents a new external force for active contours, which is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image, and has a large capture range and is able to move snakes into boundary concavities.
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Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI
Peter J. Basser,Carlo Pierpaoli +1 more
TL;DR: Quantitative-diffusion-tensor MRI consists of deriving and displaying parameters that resemble histological or physiological stains, i.e., that characterize intrinsic features of tissue microstructure and microdynamics that are objective, and insensitive to the choice of laboratory coordinate system.
Journal ArticleDOI
The design and use of steerable filters
TL;DR: The authors present an efficient architecture to synthesize filters of arbitrary orientations from linear combinations of basis filters, allowing one to adaptively steer a filter to any orientation, and to determine analytically the filter output as a function of orientation.
Journal ArticleDOI
Inversion of seismic reflection data in the acoustic approximation
TL;DR: In this paper, the nonlinear inverse problem for seismic reflection data is solved in the acoustic approximation, which is based on the generalized least squares criterion, and it can handle errors in the data set and a priori information on the model.