Estimation of the distribution function f and potential of hot stellar systems from kinematical data is discussed. When the functional forms of f and are not speciied a priori, accurate estimation of either function requires very high quality data : either accurate \line prooles" at radii extending well beyond an eeective radius, or large samples (N > 10 3) of discrete radial velocities. Estima...

In this paper, we propose a technique for determining a source term in an inverse heat conduction problem (IHCP) using Radial Basis Functions (RBFs). Because of being very suitable instruments, the RBFs have been applied for solving Partial Dierential Equations (PDEs) by some researchers. In the current study, a stable meshless method will be pro- posed for solving an (I...

generally, the presence of noise in geophysical measurements is inevitable and depending on the type and the level it affects the results of geophysical studies. so, denoising is an important part of the processing of geophysical data. on the other hand, geophysicists make inferences about the physical properties of the earth interior based on the indirect measurements (data) collected at or ne...

Over the last two decades, anomalous diffusion processes in which the mean squares variance grows slower or faster than that in a Gaussian process have found many applications. At a macroscopic level, these processes are adequately described by fractional differential equations, which involves fractional derivatives in time or/and space. The fractional derivatives describe either history mechan...

We introduce a new paradigm for solving regularized variational problems. These are typically formulated to address ill-posed inverse problems encountered in signal and image processing. The object...

Inverse elastic-wave scattering problems are shown to be ill-posed in general. Standard simplifying assumptions--the first Born approximation, the physical optics approximation, and the stopping power approximation of tomography--are shown to reduce to the same ill-posed mathematical problem, that of inverting a Fourier transform. Practical implications of this fact are illustrated with examples.

We address the problem of prior matrix estimation for the solution of `1-regularized ill-posed inverse problems. From a Bayesian viewpoint, we show that such a matrix can be regarded as an influence matrix in a multivariate `1-Laplace density function. Assuming a training set is given, the prior matrix design problem is cast as a maximum likelihood term with an additional sparsity-inducing term...

The inverse analysis is encountered in various branches of science and engineering. In the field of heat transfer, inverse analysis is used for the estimation of surface conditions such as temperature and heat flux. Also, the determination of thermal properties such as thermal conductivity and heat capacity of solids by utilizing transient temperature measurements collected from points within t...