1000 resultados para signal restoration


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A new interpolation technique has been developed for replacing missing samples in a sampled waveform drawn from a stationary stochastic process, given the power spectrum for the process. The method works with a finite block of data and is based on the assumption that components of the block DFT are Gaussian zero-mean independent random variables with variance proportional to the power spectrum at each frequency value. These assumptions make the interpolator particularly suitable for signals with a sharply-defined harmonic structure, such as audio waveforms recorded from music or voiced speech. Some results are presented and comparisons are made with existing techniques.

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With a view to solve the problems in modern information science, we put forward a new subject named High-Dimensional Space Geometrical Informatics (HDSGI). It builds a bridge between information science and point distribution analysis in high-dimensional space. A good many experimental results certified the correctness and availability of the theory of HDSGI. The proposed method for image restoration is an instance of its application in signal processing. Using an iterative "further blurring-debluring-further blurring" algorithm, the deblured image could be obtained.

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With a view to solve the problems in modern information science, we put forward a new subject named High-Dimensional Space Geometrical Informatics (HDSGI). It builds a bridge between information science and point distribution analysis in high-dimensional space. A good many experimental results certified the correctness and availability of the theory of HDSGI. The proposed method for image restoration is an instance of its application in signal processing. Using an iterative "further blurring-debluring-further blurring" algorithm, the deblured image could be obtained.

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A novel geometric algorithm for blind image restoration is proposed in this paper, based on High-Dimensional Space Geometrical Informatics (HDSGI) theory. In this algorithm every image is considered as a point, and the location relationship of the points in high-dimensional space, i.e. the intrinsic relationship of images is analyzed. Then geometric technique of "blurring-blurring-deblurring" is adopted to get the deblurring images. Comparing with other existing algorithms like Wiener filter, super resolution image restoration etc., the experimental results show that the proposed algorithm could not only obtain better details of images but also reduces the computational complexity with less computing time. The novel algorithm probably shows a new direction for blind image restoration with promising perspective of applications.

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Cardiovascular gene therapy is a novel approach to the treatment of diseases such as congestive heart failure (CHF). Gene transfer to the heart would allow for the replacement of defective or missing cellular proteins that may improve cardiac performance. Our laboratory has been focusing on the feasibility of restoring beta-adrenergic signaling deficiencies that are a characteristic of chronic CHF. We have now studied isolated ventricular myocytes from rabbits that have been chronically paced to produce hemodynamic failure. We document molecular beta-adrenergic signaling defects including down-regulation of myocardial beta-adrenergic receptors (beta-ARs), functional beta-AR uncoupling, and an up-regulation of the beta-AR kinase (betaARK1). Adenoviral-mediated gene transfer of the human beta2-AR or an inhibitor of betaARK1 to these failing myocytes led to the restoration of beta-AR signaling. These results demonstrate that defects present in this critical myocardial signaling pathway can be corrected in vitro using genetic modification and raise the possibility of novel inotropic therapies for CHF including the inhibition of betaARK1 activity in the heart.

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An analysis is carried out, using the prolate spheroidal wave functions, of certain regularized iterative and noniterative methods previously proposed for the achievement of object restoration (or, equivalently, spectral extrapolation) from noisy image data. The ill-posedness inherent in the problem is treated by means of a regularization parameter, and the analysis shows explicitly how the deleterious effects of the noise are then contained. The error in the object estimate is also assessed, and it is shown that the optimal choice for the regularization parameter depends on the signal-to-noise ratio. Numerical examples are used to demonstrate the performance of both unregularized and regularized procedures and also to show how, in the unregularized case, artefacts can be generated from pure noise. Finally, the relative error in the estimate is calculated as a function of the degree of superresolution demanded for reconstruction problems characterized by low space–bandwidth products.

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The HS1 protein is one of the major substrates of non-receptor-type protein-tyrosine kinases and is phosphorylated immediately after crosslinking of the surface IgM on B cells. The mouse B-lymphoma cell line WEHI-231 is known to undergo apoptosis upon crosslinking of surface IgM by anti-IgM antibodies. Variants of WEHI-231 that were resistant to anti-IgM-induced apoptosis expressed dramatically reduced levels of HS1 protein. Expression of the human HS1 protein from an expression vector introduced into one of the variant cell lines restored the sensitivity of the cells to apoptosis induced by surface IgM crosslinking. These results suggest that HS1 protein plays a crucial role in the B-cell antigen receptor-mediated signal transduction pathway that leads to apoptosis.