Numerical dispersion in finite difference modeling produces coherent artifacts, severely constraining the resolution of advanced imaging and inversion schemes. Conventionally, we deal with this by increasing the order of accuracy of the finite difference operators and resign ourselves to paying the high computational cost that incurs. But is there a way to reduce such dispersion without increas...

[1] This paper uses sequential Bayesian techniques such as particle filters and smoothers to track in time both the non-volcanic tremor (NVT) source location on the plate interface and the angle of arrival via horizontal phase slowness. Sequential Bayesian techniques enable tracking of evolving geophysical parameters via sequential tremor observations. These techniques provide a formulation whe...

For least mean-square (LMS) algorithm applications, it is important to improve the speed of convergence vs the residual error trade-off imposed by the selection of a certain value for the step size. In this paper, we propose to use a mixture approach, adaptively combining two independent LMS filters with large and small step sizes to obtain fast convergence with low misadjustment during station...

This paper deals with the problems of robust H2 and H∞ filtering for a class of linear continuous-time systems subject to uncertain constant parameters and both additive and state-dependent noise signals. The uncertain parameters appear affinely in the matrices of the system state-space model and are assumed to belong to a given polytope. Linear matrix inequality approaches are proposed for des...

The econometric methods of signal extraction that are based on linear filters have attained a high level of sophistication. They have now coalesced into two distinct categories. In the first category are the methods that are favoured by the central statistical agencies of many of the OECD counties. These were developed in the North American agencies, notably in Statistics Canada (Dagum 1980) an...