The fast wavelet X-ray transform

The wavelet X-ray transform computes one-dimensional wavelet transforms along lines in Euclidian space in order to perform a directional time-scale analysis of functions in several variables. A fast algorithm is proposed which executes this transformation starting with values given on a cartesian grid that represent the underlying function. The algorithm involves a rotation step and wavelet analysis/synthesis steps. The number of computations required is of the same order as the number of data involved. The analysis/synthesis steps are executed by the pyramid algorithm which is known to have this computational advantage. The rotation step makes use of a wavelet interpolation scheme. The order of computations is limited here due to the localization of the wavelets. The rotation step is executed in an optimal way by means of quasi-interpolation methods using (bi-)orthogonal wavelets

Fast algorithm for directional time-scale analysis using wavelets

Fast algorithms performing time-scale analysis of multivariate functions are discussed. The algorithms employ univariate wavelets and involve a directional parameter, namely the angle of rotation. Both the rotation steps and the wavelet analysis/synthesis steps in the algorithms require a number of computations proportional to the number of data involved. The rotation and wavelet techniques are used for the segregation of wanted and unwanted components in a seismic signal. As an illustration, the rotation and wavelet methods are applied to a synthetic shot record

Numerical methods for decomposition of 2D signals by rotation and wavelet techniques

Segregation of desirable and undesirable components in a signal given by measurements is a broad subject with many applications of huge importance. We focus on the problem that the signal to be detected is superposed by polluting signals which are characterized by a large amplitude and a few dominant directions. Such problems occur for instance in the analysis of seismic signals. We devise numerical algorithms which combine rotation of the given data with one-dimensional and two-dimensional discrete wavelet decomposition techniques respectively. The numerical algorithms are tested on both real and synthetic datasets and are compared with more classical techniques based on Fourier transforms

4pi Models of CMEs and ICMEs

Coronal mass ejections (CMEs), which dynamically connect the solar surface to the far reaches of interplanetary space, represent a major anifestation of solar activity. They are not only of principal interest but also play a pivotal role in the context of space weather predictions. The steady improvement of both numerical methods and computational resources during recent years has allowed for the creation of increasingly realistic models of interplanetary CMEs (ICMEs), which can now be compared to high-quality observational data from various space-bound missions. This review discusses existing models of CMEs, characterizing them by scientific aim and scope, CME initiation method, and physical effects included, thereby stressing the importance of fully 3-D ('4pi') spatial coverage.Comment: 14 pages plus references. Comments welcome. Accepted for publication in Solar Physics (SUN-360 topical issue

Concert jazz band concert

Thad Jonesarr. Peter GreenHorace Silver, arr. Greg HopkinsStanley Clarke, arr. Tony KlatkaBilly Strayhorn, arr. Phil WilsonBill HolmanBob Brookmeye