algorithms 
Previously, only algorithms for linearly reductive groups and for finite groups have been known.


Similar transforms may be defined on homogeneous spaces; in that case we show how special function properties of spherical functions lead to more efficient algorithms.


These results may all be viewed as generalizations of the fast Fourier transform algorithms on the circle, and of recent results about Fourier transforms on finite groups.


For the analogs of the heat and wave equation, we give algorithms for approximating the solution, and display the results of implementing these algorithms.


We use the decomposition of a group into double cosets and a graph theoretic indexing scheme to derive algorithms that generalize the CooleyTukey FFT to arbitrary finite group.


We apply our general results to special linear groups and low rank symmetric groups, and obtain new efficient algorithms for harmonic analysis on these classes of groups, as well as the twosphere.


Greedy algorithms and bestmterm approximation with respect to biorthogonal systems


The article extends upon previous work by Temlyakov, Konyagin, and Wojtaszczyk on comparing the error of certain greedy algorithms with that of best mterm approximation with respect to a general biorthogonal system in a Banach space X.


Convergence of Some Greedy Algorithms in Banach Spaces


Riesz property plays an important role in any waveletbased compression algorithm and is critical for the stability of any waveletbased numerical algorithms.


We study greedy algorithms in a Banach space from the point of view of convergence and rate of convergence.


We concentrate on studying algorithms that provide expansions into a series.


Iterative Algorithms to Approximate Canonical Gabor Windows: Computational Aspects


Also, we can obtain spherical wavelets with small support, a fact which is crucial in working with large amounts of data, since the algorithms deal with sparse matrices.


Recently, fast and reliable algorithms for the evaluation of spherical harmonic expansions have been developed.


Two fast algorithms are also presented for the analysis of signals on the sphere with steerable wavelets.


A multiresolution analysis is formulated enabling a fast wavelet transform similar to the algorithms known from classical tensor product wavelet theory.


The analyticity of functions from the RKHS enables us to derive some estimates for the covering numbers which form an essential part for the analysis of some algorithms in learning theory.


More particularly, Genetic Algorithms, Artificial Neural Networks and Fuzzy Logic methods seem to be the most promising tools to speed up and optimize the search for new leads and focused libraries.


In this paper we give a formula for enumerating the equivalent classes of orderly labeled Hamiltonian graphs under groupDn and two algorithms for constructuring these equivalent classes and all nonisomorphic Hamiltonian graphs.

