294,467 research outputs found
Power spectral estimation algorithms
Algorithms to estimate the power spectrum using Maximum Entropy Methods were developed. These algorithms were coded in FORTRAN 77 and were implemented on the VAX 780. The important considerations in this analysis are: (1) resolution, i.e., how close in frequency two spectral components can be spaced and still be identified; (2) dynamic range, i.e., how small a spectral peak can be, relative to the largest, and still be observed in the spectra; and (3) variance, i.e., how accurate the estimate of the spectra is to the actual spectra. The application of the algorithms based on Maximum Entropy Methods to a variety of data shows that these criteria are met quite well. Additional work in this direction would help confirm the findings. All of the software developed was turned over to the technical monitor. A copy of a typical program is included. Some of the actual data and graphs used on this data are also included
Spectral Algorithms for MRA Orthonormal Wavelets
ProducciĂłn CientĂficaOperator techniques lead to spectral algorithms to compute scaling
functions and wavelets associated with multiresolution analyses (MRAs). The
spectral algorithms depend on the choice of pairs of suitable orthonormal
bases (ONBs). This work presents the spectral algorithms for three different
pairs of ONBs: Haar bases, WalshâPaley bases and trigonometric bases. The
WalshâPaley bases connect wavelet theory and dyadic harmonic analysis. The
results for trigonometric bases are the first viable attempt to do a discrete
Fourier analysis of the problem.MINECO MTM2012-31439 and MTM2014-57129- C2-1-
Fingerprint Verification Using Spectral Minutiae Representations
Most fingerprint recognition systems are based on the use of a minutiae set, which is an unordered collection of minutiae locations and orientations suffering from various deformations such as translation, rotation, and scaling. The spectral minutiae representation introduced in this paper is a novel method to represent a minutiae set as a fixed-length feature vector, which is invariant to translation, and in which rotation and scaling become translations, so that they can be easily compensated for. These characteristics enable the combination of fingerprint recognition systems with template protection schemes that require a fixed-length feature vector. This paper introduces the concept of algorithms for two representation methods: the location-based spectral minutiae representation and the orientation-based spectral minutiae representation. Both algorithms are evaluated using two correlation-based spectral minutiae matching algorithms. We present the performance of our algorithms on three fingerprint databases. We also show how the performance can be improved by using a fusion scheme and singular points
Fast algorithms for computing the Boltzmann collision operator
The development of accurate and fast numerical schemes for the five fold
Boltzmann collision integral represents a challenging problem in scientific
computing. For a particular class of interactions, including the so-called hard
spheres model in dimension three, we are able to derive spectral methods that
can be evaluated through fast algorithms. These algorithms are based on a
suitable representation and approximation of the collision operator. Explicit
expressions for the errors in the schemes are given and spectral accuracy is
proved. Parallelization properties and adaptivity of the algorithms are also
discussed.Comment: 22 page
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