This note provides complete details of the numerical algorithm implemented in the software package for signal resortoration of seismic signals [5]. The complete software package is available electronically [6].

Nonparametric estimation of a density from contaminated data is a difficult problem, for which convergence rates are notoriously slow. We introduce parametrically assisted nonparametric estimators which can dramatically improve on performance of standard nonparametric estimators when the assumed model is close to the true density, without degrading much the quality of purely nonparametric estim...

This paper considers two nonlocal regularizations for image recovery, which exploit the spatial interactions in images. We get superior results using preprocessed data as input for the weighted functionals. Applications discussed include image deconvolution and tomographic reconstruction. The numerical results show our method outperforms some previous ones.

Cocktail-party Problems (increasing generality): • Independent component analysis (ICA) [1, 2]: onedimensional sound sources. • Independent subspace analysis (ISA) [3]: independent groups of people. • Blind source deconvolution (BSD) [4]: one-dimensional sound sources and echoic room. • Blind subspace deconvolution (BSSD) [5]: independent source groups and echoes. Separation Theorem: • ISA ([3]...

The Spectral Deconvolution Analysis Tool (SDAT) is being written to improve counting statistics and detection limits for nuclear explosion radionuclide measurements. SDAT will utilize spectral deconvolution spectroscopy techniques to analyze both β−γ coincidence spectra for radioxenon isotopes and high-resolution High Purity Germanium (HPGe) spectra that are utilized for aerosol monitoring. Spe...

We describe and apply an iterative, t ime-domain deconvolution approach to receiver-function estimation and illustrate the reliability and advantages of the technique using syntheticand observation-based examples. The iterative technique is commonly used in earthquake t ime-function studies and offers several advantages in receiver-function analysis such as intuitively stripping the largest rec...

Psychophysiological interaction (PPI) is a regression based method to study task modulated brain connectivity. Despite its popularity in functional MRI (fMRI) studies, its reliability and reproducibility have not been evaluated. We investigated reproducibility and reliability of PPI effects during a simple visual task, and examined the effect of deconvolution on the PPI results. A large open-ac...

The rapid accumulation of continuous paleomagnetic and rock magnetic records acquired from pass-through measurements on superconducting rock magnetometers (SRM) has greatly contributed to our understanding of the paleomagnetic field and paleo-environment. Pass-through measurements are inevitably smoothed and altered by the convolution effect of SRM sensor response, and deconvolution is needed t...

This paper introduces a framework based on the LMS algorithm for sequential deconvolution of images acquired by a pushbroom hyperspectral imaging system. Considering a sequential model of image blurring phenomenon, we derive a zero-attracting LMS (ZA-LMS) algorithm for 2D image deconvolution. Its transient behavior is analyzed in the mean and mean-square sense. For hyperspectral images, a spect...

This study attempts to develop a time-scale deconvolution filter for optimal signal reconstruction of nonstationary processes with a stationary increment transmitted through a multipath fading and colored noisy channel with stochastic tap coefficients. A deconvolution filter based on wavelet analysis/synthesis filter bank is proposed to solve this problem via a three-stage filter bank. A fracta...