Deconvolution results for the unitary EPSPs
Results On A-Unitary, A-Normal and A-Hyponormal Operators
... Remark 2.8: The products (composites) and sequences of self-adjoint operators in many instances appear in applications of analysis. Related generalizations for these are seen in ([6], Theorems 3.10.4 and 3.10.5) and they ...
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Expression Profiles of psbA, ALS, EPSPS, and Other Chloroplastic Genes in Response to PSII , ALS , and EPSPS Inhibitor Treatments in Kochia scoparia
... The results show that herbicide treatments not only affect the respec- tive target-site gene expression, but also influence the genes involved in the critical photosynthetic ...
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Supersonic Retropropulsion Experimental Results from the NASA Langley Unitary Plan Wind Tunnel
... Center Unitary Plan Wind Tunnel Test Section 2 over the Mach number range from ...Preliminary results and observations from the test are presented, while detailed data and uncertainty analyses are ...
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Implementing unitary 2-designs using random diagonal-unitary matrices
... a unitary 2-design [9, 8, 14], but is not as efficient as a recently discovered near-linear construction of an exact unitary 2-design ...a unitary 2-design has another merit in view of commutativity ...
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Efficient Deconvolution Algorithm
... The results for proposed algorithm and comparison with various deconvolution techniques are illustrated in Fig ...corresponding results are demonstrated in Fig 13 and Fig 14 ...
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Joint deconvolution and demosaicing
... , (18) where K is the number of pixels, ˆx and x are respectively the restored and the true images. Here the signal is assigned to the original im- age and the noise corresponds to the reconstruction error. Thus, the ...
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CiteSeerX — Unitary graphs
... 2 Unitary graphs In order to make this paper reasonably self-contained, we first gather basic definitions and results on unitary groups and Hermitian ...on unitary groups and Hermitian ...
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Diffusion Tractography Biomarkers of Pediatric Cerebellar Hypoplasia/Atrophy: Preliminary Results Using Constrained Spherical Deconvolution
... Limitations This study was performed in the context of a clinical MR imaging examination. Due to the need for a short acquisition time, we were able to apply only 30 gradient directions. This number of directions is too ...
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Discrete Tomography in Discrete Deconvolution: Deconvolution of Binary Images Using Ryser s Algorithm
... Fig. 4. Typical setup of a digital holographic data storage system are input to the system via a spatial light modulator (SLM) and in the simplest case, each bit is mapped to a single SLM pixel. Several data pages are ...
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Multiscale inference for multivariate deconvolution
... technical results. 2. Multiscale inference in multivariate deconvolution Let ∂ s denote the directional derivative in the direction of s ∈ S d−1 = {s ∈ R d | s = 1} and φ : R d → R ≥ 0 be a sufficiently ...
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A study in beamforming and DAMAS deconvolution
... A calibration function is made, which compensates for this off result, so the peak level method can also be used to find the strength of line sources. This calibration function is made for several coherent lengths. Also ...
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Multiscale inference for multivariate deconvolution
... nκ 1 n (0.05) of the test (4.3). The density f ε is defined in (4.1). for the sample sizes n = 500, 1000, 4000 observations and h 0 = 0.5. Here, the value of the parameter of the Laplacian error density has been chosen ...
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ANISOTROPIC ADAPTIVE KERNEL DECONVOLUTION
... multidimensional deconvolution problem; we can only mention Youndjé and Wells (2008) who consider a cross-validation method for bandwidth selection in an isotropic and ordinary smooth ...their results with ...
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Blind Deconvolution with Model Discrepancies
... In this paper, we present a novel enhanced low rank prior for blind image deblurring. The low rank properties of both intensity and gradient maps from image patches are exploited in the proposed algorithm. We present a ...
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Anisotropic adaptive kernel deconvolution
... multidimensional deconvolution problem; we can only mention Masry [1991] who considers mainly the problem of dependency between the variables without anisotropy nor adaptation, and Youndjé and Wells [2008] who ...
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Undercomplete Blind Subspace Deconvolution
... undercomplete version (uBSSD) of the task has been presented, and it has been shown how to derive an independent subspace analysis (ISA) task from the uBSSD problem. Recent developments of the ISA techniques enabled us ...
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Revisiting Bayesian Blind Deconvolution
... non-blind deconvolution problem is also harder), the SSD ratio between the image deconvolved with the estimated kernel and the image deconvolved with the ground-truth kernel is used as the final evaluation ...
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A ridge-parameter approach to deconvolution
... gives results broadly similar to those for n = 400 in case ...show results for the kernel estimator in the setting of Figures 1 and 2 ...these results has Fourier transform (1 − t 2 ) 3 for |t| ≤ 1; ...
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Density deconvolution with epi-splines
... of deconvolution problems through constrained optimization with first-order epi-splines, which are used for the first time to approximate densities to an arbitrarily high level of ...dynamics. Results show ...
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Unitary thrifts: a performance analysis
... Non-UTHC thrifts appear to have lower ROA if they rely more heavily on fee income for revenues (FEESHR is negative and significant). One should be careful, however, in interpreting these results in terms of ...
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