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https://www.nist.gov/people/alfred-s-carasso
Alfred S Carasso (Fed)
Achievements include significant contributions to the deconvolution problem; and to such related areas of mathematical analysis as ill-posed continuation, time-reversed parabolic nist-equations, holomorphic semigroup theory, and first kind integral nist-equations; invention of slowly divergent schemes and backward beam formalism for solving inverse diffusion nist-equations; invention of stabilized explicit time-marching computational schemes for multidimensional, nonlinear, ill-posed, backward parabolic nist-equations; invention of APEX and BEAK methods in blind image deconvolution; development of SECB constraint for extensive class of ill-posed PDE problems; creation of Poisson singular integral method in Lipschitz space characterization and recovery of non smooth imagery; applications in system identification, nondestructive evaluation, inverse heat transfer, image reconstruction;enhancement of Helium ion microscope nanoscale imagery, and of forensic latent fingerprints; discovery of useful property of ill-posed, time-reversed, fractional and logarithmic diffusion nist-equations, in blind deconvolution of Hubble space telescope imagery, scanning electron micrographs, MRI and PET brain scans; patented image reconstruction procedures.
This paper considers the ill-posed data assimilation problem associated with hyper- bolic/parabolic systems describing 2D coupled sound and heat flow. Given
With an artificial example of a 2D nonlinear advection diffusion equation on the unit square this paper considers the data assimilation problem of finding
Richardson's leapfrog scheme is notoriously unconditionally unstable in well-posed, forward, linear dissipative evolution equations. Remarkably, that scheme can
Abstract. This paper constructs an unconditionally stable explicit difference scheme, marching backward in time, that can solve an interesting, but limited