An optimal algorithm is described for solving the deconvolution problem of the form ku := ∫ t 0 k(t − s)u(s)ds = f(t) given the noisy data fδ, ||f − fδ|| ≤ δ. The idea of the method consists of the representation k = A(I+S), where S is a compact operator, I + S is injective, I is the identity operator, A is not boundedly invertible, and an optimal regularizer is constructed for A. The optimal r...

In the popular deconvolution problem, the goal is to estimate a curve f from data that only allow direct estimation of another curve g, the convolution of f and a so-called error density. Unlike the standard assumption in deconvolution, we consider a more general setting where the characteristic function of the error density can have zeros. This problem is important as the characteristic functi...

Abstract Fluorescence live cell microscopy is central to the analysis of inter- and intracellular signaling. However, highly dynamic, local processes requires high temporal spatial resolution imaging, which intrinsically linked a low signal-to-noise ratio. To improve image quality after data acquisition, computational techniques, referred as deconvolution, are being developed. Here, we discuss ...

Hormone secretion is an intrinsically discontinuous process characterized by a pul-satile pattern. In this paper we describe a fuzzy deconvolution method for pulsatile hormone secretion signals. The secretion signal is modeled as a Poisson process. The fuzzy deconvolution method is based on fuzzy identiication by using learning signals, mountain clustering and optimal output predefuzziication. ...

This paper proposes nonparametric deconvolution density estimation over S 2. Here we would think of the S 2 elements of interest being corrupted by random SO(3) elements (rotations). The resulting density on the observations would be a convolution of the SO(3) density with the true S 2 density. Consequently, the methodology, as in the Euclidean case, would be to use Fourier analysis on SO(3) an...

BACKGROUND The challenge in systematic toxicological analysis using gas chromatography and/or liquid chromatography coupled to mass spectrometry is to identify compounds of interest from background noise. The large amount of spectral information collected in one full-scan MS run demands the use of automated evaluation of recorded data files. We evaluated the applicability of the freeware deconv...

Seismic interferometry is a field of growing interest in exploration seismology. In this paper we provide the theoretical basis for performing interferometry by deconvolution. We argue that for general models, deconvolution interferometry gives only the causal scattering response between any two receivers, as opposed to cross-correlation which gives both causal and acausal scattering responses....

Background First pass perfusion CMR is a well-validated technique for the detection of inducible myocardial ischaemia. However, limited data are available on the feasibility of first pass perfusion CMR and quantitative deconvolution analysis in the context of reduced LV function. The aim of this study was to assess effects of reduced LV function and LV dilatation on the characteristics of signa...

introduction: renal dynamic study is a well-established and popular test in routine practice of nuclear medicine. the test is non-invasive, rapid and unique in evaluation of the kidney function. in despite of its clinical values, the parameters derived from renogram are physiologically meaningless. that is due to the fact that renogram is not the true kidney function. from mathematical points o...