This study uses 35 pesticides spiked in spinach extracts at the 50 ppb level to find the optimal AMDIS deconvolution settings. Additional advantages of using deconvolution versus MSD ChemStation, to find more compounds in an extract are also discussed. The detectability of compounds in a complex matrix is significantly improved with deconvolution. This can also be viewed as better or increased ...

Two approaches to the combination of robust variational deconvolution with positivity constraints are considered. The first approach modifies a standard robust variational deconvolution method by carrying out a gradient descent with respect to a multiplicative perturbation, which can also be considered as gradient descent in a hyperbolic metric. The second approach is based on the representatio...

Deconvolution is an image restoration technique which improves image contrast, resolution and signal to noise ratio. In modern optical microscopy and biological research deconvolution is becoming a fundamental processing step which allows for better image analysis. Deconvolution remains however a challenging task as the result depends strongly on the algorithm chosen, the parameters settings an...

This paper proposes an adaptive microphone array using blind deconvolution. The method realizes an signal enhancement based on the combination with beamforming using blind deconvolution, synchronized summation and DSA method. The proposed method improves a performance of estimation by the iterative operation of blind deconvolution using a cost-function base on the coherency function.

This paper discusses blind identification and deconvolution of two-input two-output channels corrupted by noises based on secondorder statistics. First, the identifiability of channel is analyzed. By constructing an new criterion, the channel parameters can be identified precisely in the present of noises. Second, the cost function of identification is established and the corresponding algorith...

We present an approach to determine sufficient conditions for the global convergence of iterative blind deconvolution algorithms using finite impulse response (FIR) deconvolution filters. The novel technique, which incorporates Lyapunov’s direct method, is general, flexible, and can be easily adapted to analyze the behavior of many types of nonlinear iterative signal processing algorithms. Spec...

The method described here performs blind deconvolution of the beamforming output in the frequency domain. To provide accurate blind deconvolution, sparsity priors are introduced with a smooth l1/l2 regularization term. As the mean of the noise in the power spectrum domain is dependent on its variance in the time domain, the proposed method includes a variance estimation step, which allows more ...

The deconvolution principle was used to evaluate the extent of absorption and first-pass elimination of selected drugs. In the first example, deconvolution of the portal blood profiles of etretinate (ET, a synthetic retinoid) indicated that there was significant gut-wall conversion of ET to acitretin (ETA, the primary metabolite of ET) during a 60-min intestinal perfusion of ET. In the second e...

Deconvoluting the molecular target signals behind observed drug response phenotypes is an important part of phenotype-based drug discovery and repurposing efforts. We demonstrate here how our network-based deconvolution approach, named target addiction score (TAS), provides insights into the functional importance of druggable protein targets in cell-based drug sensitivity testing experiments. U...