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Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 292 for “"Deconvolution"”.
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Approximate Deconvolution Reduced Order Modeling
… define the large ROM structures. An approximate deconvolution (AD) approach is used to solve the ROM closure problem and develop a new AD-ROM. This AD-ROM is tested in the numerical simulation of the one-dimensional Burgers equation with a small diffusion coefficient ( ν= 10⁻³).
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PSF Sampling in Fluorescence Image Deconvolution
… to restoring the image resolution is to use a deconvolution algorithm to “invert” the effect of convolving the volume with the point spread function. However, these algorithms fall short in several areas such as noise amplification and stopping criterion. In this paper, we try to reconstruct an …
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Deconvolution and sparsity based image restoration
Deconvolution and sparse representation are the two key areas in image and signal processing. In this thesis the classical image restoration problem is addressed using these two modalities. Image restoration, such as deblurring, dnoising, and in-painting belongs to the class of ill-posed linear …
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Deconvolution and sparsity based image restoration
Deconvolution and sparse representation are the two key areas in image and signal processing. In this thesis the classical image restoration problem is addressed using these two modalities. Image restoration, such as deblurring, dnoising, and in-painting belongs to the class of ill-posed linear …
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Frequency-domain deconvolution in deep learning
… in computer vision tasks: the frequency-domain deconvolution operation. Recognizing the unparalleled success of convolutional neural networks (CNNs) in the realm of computer vision, we critically evaluate the performance and computational demands of traditional convolution operations against the …
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Comparison of receiver function deconvolution techniques
… Due to the presence of noise in the data, the deconvolution is unstable and must be regularized. Six deconvolution techniques are evaluated and compared based on their performance with synthetic data sets. These methods approach the deconvolution problem from either the frequency or time …
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An EM algorithm for Lidar deconvolution
… convolved distortion of the ground return. Deconvolution is one approach to restore the original ground return from the observed return signal. The expectation-maximization (EM) algorithm has been used in signal deconvolution, to produce a maximum-likelihood estimate (MLE) for the original …
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Multichannel blind deconvolution in underwater acoustic channels
… techniques for solving the multichannel blind deconvolution problem and implemented these techniques in acoustic waveguide multiple environment. We developed a systematic way to build an efficient and accurate channel models incorporating a priori information about the expected Channel Impulse …
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Image Deconvolution Techniques for Single Molecule Studies
… single molecule studies by:: i) developing deconvolution techniques in order to localize both immobile and dynamic molecules from their single images with improved spatial and temporal resolution,: ii) determining a protein's diffusive properties with high temporal resolution, and: iii) …
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Deconvolution of Membrane Protein-Detergent Complex Interactions
<p>Membrane proteins are important in many biological functions such as cell-cell recognition, transport, and signaling; yet the study of these proteins is stunted due to their excessive aggregation in aqueous solutions. Detergents have been extensively exploited to mitigate this aggregation, and …
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Digital Deconvolution: Image Sampling and Restoration Techniques
Made available in DSpace on 2014-12-12T20:54:18Z (GMT). No. of bitstreams: 1 7606996.pdf: 3680460 bytes, checksum: cf83d4bf45c2b238b468fed98a7f39db (MD5) Previous issue date: 1975
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Blind Multichannel Image Deconvolution and Optimum Sparse Approximations
The second problem is one of computing maximally sparse elements of a convex, compact set. This problem arises in a wide range of engineering applications, including regularization of ill-posed problems, design of digital filters with few non-zero coefficients and the computation of sparse …
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Deconvolution of Leukemic Evolution Through Initiation, Progression and Relapse
Significant advancements in the study of the genomic architecture of B-cell acute lymphoblastic leukemia (B-ALL) have been made, but our understanding of the mechanisms of leukemic initiation and progression remain limited. To gain clarity on these processes, a deeper understanding of the …
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Cramer-Rao bound analysis of multi-frame blind deconvolution
… and multiple frames affect multi-frame blind deconvolution. Previous research in non-blind deconvolution, which seeks to estimate an object from a blurred and noisy image, characterized how the use of support constraints exploited spatial noise correlations to reduce noise in the estimate of …
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The Fourier convolution-deconvolution method: its limitation and application
… paramagnetic resonance (EPR) Fourier Convolution-Deconvolution method of measuring distance was utilized to determine the distance between two cysteine mutated residues in the linker region of Sso1p in order to determine the conformation of this region during SNARE complex assembly. A 12 -14 …
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Deconvolution of spatiotemporal transcriptomic heterogeneity in the glioblastoma ecosystem
… computational framework based on unsupervised deconvolution, I characterize a compendium of 15 tumor cell gene expression programs set within the context of 90 mouse brain and TME cell types, cell activities, and anatomic structures. This approach reveals the spatial organization of tumor …
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Global deconvolution of heterotropic cooperativity in cytochrome P450 3A4
Cytochrome P450 3A4 (CYP3A4) plays a central role in xenobiotic metabolism, and is of critical importance to both human health and the pharmaceutical industry. Its ability to interact with multiple molecules of the same substrate, or multiple substrates, leads to complex non-Michaelis kinetics, …
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Unsupervised Signal Deconvolution for Multiscale Characterization of Tissue Heterogeneity
… and genomic profiling methods. While signal deconvolution has widespread applications in many real-world problems, there are significant limitations associated with existing methods, mainly unrealistic assumptions and heuristics, leading to inaccurate or incorrect results. In this study, we …
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