2011
DOI: 10.1007/s13137-011-0016-z
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Spatiospectral concentration in the Cartesian plane

Abstract: We pose and solve the analogue of Slepian's time-frequency concentration problem in the two-dimensional plane, for applications in the natural sciences. We determine an orthogonal family of strictly bandlimited functions that are optimally concentrated within a closed region of the plane, or, alternatively, of strictly spacelimited functions that are optimally concentrated in the Fourier domain. The Cartesian Slepian functions can be found by solving a Fredholm integral equation whose associated eigenvalues ar… Show more

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Cited by 57 publications
(53 citation statements)
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“…It is difficult to compare spatial resolution between modeling approaches without detailed considerations to quantify bias, variance, signal-to-noise ratios, and the effect of bandwidth selection Slobbe et al, 2012). Nevertheless, a detailed comparative study by Longuevergne et al (2010), carried out on the scale of hydrological basins, independently of our own efforts, was indicative of favorable behavior of the approaches based on Slepian functions.…”
Section: Assessing Spatial Resolutionmentioning
confidence: 99%
See 1 more Smart Citation
“…It is difficult to compare spatial resolution between modeling approaches without detailed considerations to quantify bias, variance, signal-to-noise ratios, and the effect of bandwidth selection Slobbe et al, 2012). Nevertheless, a detailed comparative study by Longuevergne et al (2010), carried out on the scale of hydrological basins, independently of our own efforts, was indicative of favorable behavior of the approaches based on Slepian functions.…”
Section: Assessing Spatial Resolutionmentioning
confidence: 99%
“…The effort in constructing the Slepian functions is minimal, as they are efficiently computed via variety of numerical methods, both on the sphere (Simons and Dahlen, 2007) and in the plane (Simons and Wang, 2011). Compared to other gravitybased approaches, we do not a priori remove correlations between spherical-harmonic coefficients (Swenson and Wahr, 2006), and neither smooth nor project on a predefined basin structure (Wouters et al, 2008;King et al, 2012;Sasgen et al, 2012Sasgen et al, , 2013.…”
Section: Assessing Spatial Resolutionmentioning
confidence: 99%
“…Since the efficient generation of Slepian functions on domains of arbitrary geometry, whether in spherical or Cartesian (Simons and Wang 2011) coordinates, presents no intrinsic difficulties, we are here able to consider their use in the context of the work by , on which we build. Our main goal is to design a bandlimited Slepian basis for the ocean basins in spherical geometry and to evaluate the utility of this basis in solving the problem stated above, which is to derive suitable representations of altimetric MSL while maintaining spectral consistency with the gravimetric geoid.…”
Section: Introductionmentioning
confidence: 99%
“…For simplicity, we use square data patches or windows. Selective methods for regions of arbitrary description, such as irregular tectonic provinces, have also been developed, and may help avoid blending contrasting T e from different features into a single estimate (Simons and Wang, 2011). However, most workers to date have used square or circular windows, making a simple geometric patch a better test domain for the reliability of existing analyses.…”
Section: Methods and Motivationmentioning
confidence: 99%