The deconvolution of a single Gaussian kernel is extended to a sum of Gaussian kernels with positive coefficients (case 1) and to a Mexican hat (case 2). In case 1 the normalization requires the sum of the normalized Gaussian kernels to be always 1, i.e. c0 + c1 + c2 + · · · = 1. Each coefficient satisfies ck > 0. In case 2 (Mexican hat) the properties c0 + c1 = 1 with c0 > 1and c1 < 0 hold; c1...

We use B-splines for representing the derivative of the unknown unit-rate drawdown pressure and numerical inversion of the Laplace transform to formulate a new deconvolution algorithm. When significant errors and inconsistencies are present in the data functions, direct and indirect regularization methods are incorporated. We provide examples of underand over-regularization, and we discuss proc...

Rotating machinery vibration analysis involves a convolute mixture because of the propagation medium, and the signals recorded by sensors in an industrial application are often disrupted by the environment. Deconvolution is a signal processing method for convolution of vibration sources, spectral kurtosis is a statistical tool which can indicate the presence of series of transients and their lo...

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures ...

Deconvolution interferometry successfully recovers the impulse response between two receivers without the need for an independent estimate of the source function. Here we extend the method of interferometry by deconvolution to multicomponent data in elastic media.As in the acoustic case, elastic deconvolution interferometry retrieves only causal scattered waves that propagate between two receiv...

The measurement process in fluorophotometry inherently involves a loss of information due to the finite sampling volume of the instrument. Mathematically, the effect is expressed as a convolution of the actual fluorescein distribution with the spread function of the instrument. Scattering by the ocular media can increase the spread function over that due to the instrument alone. A method is pro...

In equalization and deconvolution tasks the correlated nature of the input signal slows the convergence speeds of the least mean square LMS and other stochastic gradient adaptive lters Prewhitening techniques have been proposed to improve convergence performance but the addi tional coe cient memory and updates for the prewhitening lter can be prohibitive in some applica tions In this report we ...

The error distribution is generally unknown in deconvolution problems with real applications. A separate independent experiment is thus often conducted to collect the additional noise data in those studies. In this paper, we study the nonparametric deconvolution estimation from a contaminated sample coupled with an additional noise sample. A ridge-based kernel deconvolution estimator is propose...

[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...

A method based on cepstral deconvolution technique is proposed for measurement of absorption and scattering coefficients of materials. The reverberation room method standardized by International Organization for Standardization (ISO) is taken as the reference for measurements. Several measurements are conducted in a physically scaled reverberation room and results are evaluated by these two met...