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Showing 1 to 20 of 55 for “"orthonormal"”.

  1. DISCRETE TRANSFORMS WITH GOOD TIME-FREQUENCY AND SPATIAL-FREQUENCY LOCALIZATION

    <p>Discrete orthonormal time-frequency basis functions are described and used for both analysis and synthesis of complex-valued signals. We derive expressions for complex-valued expansion coefficients in time-frequency lattices in the discrete one dimensional case. This derivation is based on …

    cuny Repository record for DISCRETE TRANSFORMS WITH GOOD TIME-FREQUENCY AND SPATIAL-FREQUENCY LOCALIZATION (opens in a new tab)

  2. Notes on generalized Fourier series with application to gravitational field determination

    Let{(}φ<sub>n</sub>(x)} be an orthonormal system in the set of Lebesgue square integrable functions L². Let f𝜖L². The generalized Fourier series of f with respect to {(}φ<sub>n</sub>(x)} is the series ∑<sub>n=0</sub><sup>∞</sup> (f, φ<sub>n</sub>) φ<sub>n</sub>(x), where (f, φ<sub>n</sub>) is the …

    vt Repository record for Notes on generalized Fourier series with application to gravitational field determination (opens in a new tab)

  3. Wavelets and filter banks: New results and applications

    … of non-stationary signals. Wavelet analysis uses orthonormal bases in which computations can be done efficiently with multirate systems known as filter banks. This thesis develops a comprehensive set of tools for (multidimensional) multirate signal analysis and uses them to investigate two …

    rice Repository record for Wavelets and filter banks: New results and applications (opens in a new tab)

  4. On the Use of Arnoldi and Golub-Kahan Bases to Solve Nonsymmetric Ill-Posed Inverse Problems

    … bidiagonalization is used to construct a set of orthonormal basis vectors that span the Krylov subspaces from which solutions will be chosen, but seeking a solution in the orthonormal basis generated by the Arnoldi process (which is fundamental to the popular iterative method GMRES) has been of …

    vt Repository record for On the Use of Arnoldi and Golub-Kahan Bases to Solve Nonsymmetric Ill-Posed Inverse Problems (opens in a new tab)

  5. Asymptotics of Carleman Polynomials for Level Curves of the Inverse of a Shifted Joukowsky Transformation

    … of the sequence of polynomials that are orthonormal over the interior domain of L with respect to the area measure. We establish strong asymptotic formulas describing the behavior of these polynomials (as their degree increases) at every point of the complex plane.

    mississippi Repository record for Asymptotics of Carleman Polynomials for Level Curves of the Inverse of a Shifted Joukowsky Transformation (opens in a new tab)

  6. A Unified Framework for Image Modeling and Estimation Using Measurement Constraints

    … from imprecise subband statistics in multiple orthonormal wavelet bases is developed. Experimental results for the problem of image restoration in additive white Gaussian noise are presented. Denoising and restoration of natural images using algorithms based on these maxent priors demonstrate …

    uiuc Repository record for A Unified Framework for Image Modeling and Estimation Using Measurement Constraints (opens in a new tab)

  7. Unique Image Representation as a Tensor

    <p>This thesis presents a two dimensional orthonormal transform that represents an image as coefficients in 4 independent channels. The salient feature of these coefficients is that they contain complete position spatial frequency information about the image, in a sense that the original image can …

    cuny Repository record for Unique Image Representation as a Tensor (opens in a new tab)

  8. Distributed Singular Value Decomposition Through Least Squares

    … and corresponding singular vectors that form orthonormal bases. SVD has wide-ranging applications from principal component analysis (PCA) to matrix completion and approximation. Methods for computing the SVD of a matrix are extensive and involve optimization algorithms with some theoretical …

    mit Repository record for Distributed Singular Value Decomposition Through Least Squares (opens in a new tab)

  9. Selection of Step Size for Total Variation Minimization in CT

    … that signals with sparse representations in an orthonormal basis may be reconstructed via l1-minimization. Furthermore, if an image can be approximately modeled to be piecewise constant, then its gradient is sparse. The application of l1-minimization to a sparse gradient, known as total …

    gsu Repository record for Selection of Step Size for Total Variation Minimization in CT (opens in a new tab)

  10. Orthogonality and convergence of discrete Zernike polynomials

    … have not been addressed. This work examines the orthonormal polynomials visually with the Gram matrix and computationally with the rank and condition number. The convergence of the Fourier-Zernike coe\ufb03cients and the Fourier-Zernike series are also examined using various measures of error. …

    unm Repository record for Orthogonality and convergence of discrete Zernike polynomials (opens in a new tab)

  11. Conjugate gradient density matrix search: A linear scaling alternative to diagonalization

    … is used to transform to and back from an orthonormal basis. Linear scaling of CPU time for the density matrix search and crossover of CPU time with diagonalization is demonstrated for polyglycine chains containing up to 493 atoms and water clusters up to 900 atoms.

    rice Repository record for Conjugate gradient density matrix search: A linear scaling alternative to diagonalization (opens in a new tab)

  12. A wavelet-based numerical scheme for stochastic mechanics

    … is an improvement over that achieved with orthonormal wavelet basis functions. It is shown that a biorthogonal dual wavelets with sufficient number of vanishing moments and corresponding to a low primal order perform better than Daubechies wavelets at this task. These observations are used …

    rice Repository record for A wavelet-based numerical scheme for stochastic mechanics (opens in a new tab)

  13. GPGPU-Enabled Physics Based Deformed Model Simulation

    … Classic modal analysis provides a set of orthonormal bases vectors, which span a spectral space encoding the dynamics of the elastic body. As each basis vector is orthogonal to each other, the computation is completely decoupled and can be well-fit into the modern GPGPU platform. We …

    unm Repository record for GPGPU-Enabled Physics Based Deformed Model Simulation (opens in a new tab)

  14. Time-series analysis using orthogonal polynomials

    … Fourier expansion of the polynomial system 11 orthonormal to the invariant measures. Programs have been written based on the MB approach and these programs were tested on various one dimensional time-series like the sine map, the tent map and the logistic map. This approach to reconstruction …

    ttu Repository record for Time-series analysis using orthogonal polynomials (opens in a new tab)

  15. Facial Expression Recognition: Fusion of A Human Vision System Model and A statistical framework

    … its variations is overcome by a novel composite orthonormal basis that separates expression from identity information. Finally, by way of bringing theory closer to practice, the proposed facial expression recognition algorithm has been efficiently implemented for a web application.

    nus Repository record for Facial Expression Recognition: Fusion of A Human Vision System Model and A statistical framework (opens in a new tab)

  16. Reduced basis method for Boltzmann equation

    … We conclude the project by verifying that the orthonormal reduced Basis method based on the greedy algorithm converges rapidly over the chosen test space.

    mit Repository record for Reduced basis method for Boltzmann equation (opens in a new tab)

  17. Tensorial Impedance Surfaces for Manipulating Microwaves

    … impedance matrix being reciprocal, passive and orthonormal. Verification is done with reflection problems that demand non-specular reflection and polarisation conversion. A metasurface design is proposed that exhibits an effective impedance that is non-orthogonal to demonstrate that the …

    exeter

  18. Learning strictly orthogonal p-order nonnegative Laplacian embedding via smoothed iterative reweighted method

    … from the input graph. Optimization with both orthonormal and nonnegative constraints is highly nonlinear and nonconvex in feasible domain. The p-order term in our objective further makes it nonsmooth and difficult to efficiently solve in general. We introduce a novel smoothed iterative …

    colo-mines Repository record for Learning strictly orthogonal p-order nonnegative Laplacian embedding via smoothed iterative reweighted method (opens in a new tab)

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