Nonparametric identification of linear systems is investigated in this paper. Nonparametric identification is the estimation of the time record of the impulse response of the system. It is a deconvolution problem, i.e., inverse operation of the convolution of the impulse response and the excitation signal. The problem is ill posed, i.e., deconvolution amplifies the measurement noise to a great ...

purpose: to determine the incidence, concurrent factors and clinical results of re-operation after corneal refractive surgeries. methods: in this retrospective descriptive study records of all patients undergoing corneal refractive surgeries including prk, lasik, and lasek between april 2005 and december 2006 were assessed. patients who had undergone re-operations entered the study; visual acui...

Introduction: Prior studies comparing Hemodynamic Response Function (HRF) in the young and elderly adults based on fMRI data have reported inconsistent findings for brain vision and motor regions in healthy aging. It is shown that the averaging method employed in all previous works has caused this inconsistency. The averaging is so sensitive to outliers and noise. However, fMRI data are o...

[1] We have completed the first global spatial deconvolution analysis of planetary gamma-ray data for lunar Th abundances as measured by the Lunar Prospector Gamma-ray Spectrometer. We tested two different spatial deconvolution techniques – Jansson’s method and the Pixon method – and determined that the Pixon method provides superior performance. The final deconvolved map results in a spatial r...

Diffusion tensor imaging (DTI) MRI is a noninvasive imaging method of the cerebral tissues whose fibers directions are not evaluated correctly in the regions of the crossing fibers. For the same reason the high angular resolution diffusion images (HARDI) are used for estimation of the fiber direction in each voxel. One of the main methods to specify the direction of fibers is usage of the spher...

case. from simultaneously rncasured rkm nholc pressure and flow Thr Cltrdfclfer ( (;larffelter. Tracy. and lf’ilwy] ) dec-nnvnlw rate, psD is alsn called “deccmvolved pressure, influence func[i(]lt rrw( hod has bwn nwd for t}Ic las( thrw decades for dr(er[ion or unif rwpunse bctlts~iur.Once p.~D is obtained. the n]ining the constant rate behavior of the ivell-rcwrvoir sys!em conventional interp...

The subject of this paper is beam deconvolution in small angular scale CMB experiments. The beam effect is reversed using the Jacobi iterative method, which was designed to solved systems of algebraic linear equations. The beam is a non circular one which moves according to the observational strategy. A certain realistic level of Gaussian instrumental noise is assumed. The method applies to sma...

3D deconvolution is a challenging problem faced by astronomers and micrsoscopists. The goal of deconvolution algorithms is to reverse the effects of convolution on the observed data. Convolution can be understood as a blurring operation on the ground truth that results in a relatively blurred/unclear observation. It is challenging to model the exact convolution operation because of various fact...

This report studies an abstract approach to modeling the motion of large eddies in a turbulent flow. If the Navier-Stokes equations (NSE) are averaged with a local, spatial convolution type filter, φ = gδ ∗ φ, the resulting system is not closed due to the filtered nonlinear term uu. An approximate deconvolution operator D is a bounded linear operator which is an approximate filter inverse D(u) ...