Abstract We present a noise deconvolution technique to remove wide class of noises when performing arbitrary measurements on qubit systems. In particular, we derive the inverse map most common single noisy channels, and exploit it at data processing step obtain noise-free estimates observables evaluated system subject known noise. illustrate self-consistency check ensure that characterization i...

In spite of the huge literature on deconvolution problems, very little is done for hybrid contexts where signals are quantized. In this paper we undertake an information theoretic approach to the deconvolution problem of a simple integrator with quantized binary input and sampled noisy output. We recast it into a decoding problem and we propose and analyze (theoretically and numerically) some l...

In this paper we discuss the semi parametric statistical model for blind deconvolution. First we introduce a Lie Group to the manifold of noncausal FIR filters. Then blind deconvolution problem is formulated in the framework of a semiparametric model, and a family of estimating functions is derived for blind deconvolution. A natural gradient learning algorithm is developed for training noncausa...

The aim of the present Letter is to introduce a new blind deconvolution algorithm based on fixed-point optimization of a ‘Bussgang’-type cost function. The cost function relies on approximate Bayesian estimation achieved by an adaptive neuron. The main feature of the presented algorithm is fast convergence that guarantees good deconvolution performances with limited computational demand compare...

Sparse deconvolution is a classical subject in digital signal processing, having many practical applications. Support vector machine (SVM) algorithms show a series of characteristics, such as sparse solutions and implicit regularization, which make them attractive for solving sparse deconvolution problems. Here, a sparse deconvolution algorithm based on the SVM framework for signal processing i...

A maximum a posteriori (MAP) approach, based on the Bayesian criterion, is proposed to overcome the low cross-range resolution problem in forward-looking imaging. We adapt scanning radar system to record received data and exploit deconvolution method to enhance the real-aperture resolution because the received echo is the convolution of target scattering coefficient and antenna pattern. The Gen...

Candida rugosa lipase (CRL) was deposited by matrix assisted pulsed laser evaporation (MAPLE) in order to immobilize the enzyme with a preserved native conformation, which ensures its catalytic functionality. For this purpose, the composition of the MAPLE target was optimized by adding the oil phase pentane to a water solution of the amino acid 3-(3,4-dihydroxyphenyl)-2-methyl-l-alanine (m-DOPA...

Introduction Several deconvolution methods have been proposed to increase the angular resolution of HARDI or QBI [1][2]. However, there is no deconvolution method directly applied to diffusion ODF without resorting to spherical decomposition. In this study, we developed a deconvolution method that could be directly applied to diffusion ODF, thus extending its applicability to other q-space meth...

The global emergence of multi-drug resistant bacteria invokes an urgent and imperative necessity for the identification of novel antimicrobials. The general lack of success in progressing novel chemical entities from target-based drug screens have prompted calls for radical and innovative approaches for drug discovery. Recent developments in chemical biology and target deconvolution strategies ...