In this work, we design complete orthonormal basis functions, which are referred to as optimal basis functions, that span the vector sum of subspaces formed by band-limited spatially concentrated and space-limited spectrally concentrated functions. The optimal basis are shown to be a linear combination of band-limited functions with maximized energy concentration in some spatial region of interest and space-limited functions which maximize the energy concentration in some spectral region. The linear combination is designed with an optimality condition of maximizing the product of measures of energy concentration in the spatial and spectral domain. We also show that each optimal basis is an eigenfunction of a linear operator which maximizes ...
We study the problem of choosing the optimal wavelet basis with compact support for signal represent...
AbstractThis paper considers the design of isotropic analysis functions on the sphere which are perf...
Abstract: This paper gives an algorithm for identifying spectral densities using orthonormal basis f...
In this work, we design a set of complete orthonormal optimal basis functions for signals defined on...
Abstract. We formulate and solve the Slepian spatial-spectral concentration problem on the three-dim...
We construct spherical vector bases that are bandlimited and spatially concentrated, or alternativel...
In this paper, we develop an analytical formulation for the Slepian spatial-spectral concentration p...
Linear inverse problems arise in biomedicine electroencephalography and magnetoencephalography (EEG ...
Signals defined on the unit sphere cannot be simultaneously concentrated in a spatial region and in ...
The problems of filtering, spectral analysis and spectral estimation have been investigated on the s...
This paper studies signal concentration in the time and frequency domains using the general constrai...
This paper introduces an adaptive, multi-resolution windowing technique that can be used in conjunct...
Increase in dimensionality of the signal space for a fixed bandwidth leads to exponential growth in ...
Increase in dimensionality of the signal space for a fixed bandwidth leads to exponential growth in ...
For the filtering of peaks in periodic signals, we specify polynomial filters that are optimally loc...
We study the problem of choosing the optimal wavelet basis with compact support for signal represent...
AbstractThis paper considers the design of isotropic analysis functions on the sphere which are perf...
Abstract: This paper gives an algorithm for identifying spectral densities using orthonormal basis f...
In this work, we design a set of complete orthonormal optimal basis functions for signals defined on...
Abstract. We formulate and solve the Slepian spatial-spectral concentration problem on the three-dim...
We construct spherical vector bases that are bandlimited and spatially concentrated, or alternativel...
In this paper, we develop an analytical formulation for the Slepian spatial-spectral concentration p...
Linear inverse problems arise in biomedicine electroencephalography and magnetoencephalography (EEG ...
Signals defined on the unit sphere cannot be simultaneously concentrated in a spatial region and in ...
The problems of filtering, spectral analysis and spectral estimation have been investigated on the s...
This paper studies signal concentration in the time and frequency domains using the general constrai...
This paper introduces an adaptive, multi-resolution windowing technique that can be used in conjunct...
Increase in dimensionality of the signal space for a fixed bandwidth leads to exponential growth in ...
Increase in dimensionality of the signal space for a fixed bandwidth leads to exponential growth in ...
For the filtering of peaks in periodic signals, we specify polynomial filters that are optimally loc...
We study the problem of choosing the optimal wavelet basis with compact support for signal represent...
AbstractThis paper considers the design of isotropic analysis functions on the sphere which are perf...
Abstract: This paper gives an algorithm for identifying spectral densities using orthonormal basis f...