The Experts below are selected from a list of 126 Experts worldwide ranked by ideXlab platform
József Bokor - One of the best experts on this subject based on the ideXlab platform.
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minimal partial realization from generalized orthonormal basis function expansions
Automatica, 2002Co-Authors: T.j. De Hoog, Z Szabo, Peter S.c. Heuberger, József BokorAbstract:A solution is presented for the problem of realizing a discrete-time LTI state-space model of minimal McMillan Degree such that its first N expansion coefficients in terms of generalized orthonormal basis match a given sequence. The basis considered, also known as the Hambo basis, can be viewed as a generalization of the more familiar Laguerre and two-parameter Kautz constructions, allowing general dynamic information to be incorporated in the basis. For the solution of the problem use is made of the properties of the Hambo operator transform theory that underlies the basis function expansion. As corollary results compact expressions are found by which the Hambo transform and its inverse can be computed efficiently. The resulting realization algorithms can be applied in an approximative sense, for instance, for computing a low-order model from a large basis function expansion that is obtained in an identification experiment.
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Minimal partial realization from orthonormal basis function expansions
Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228), 2001Co-Authors: Peter S.c. Heuberger, Z Szabo, T.j. De Hoog, József BokorAbstract:Given an expansion of a dynamical system in terms of a generalized orthonormal (Hambo) basis, the problem of realizing a state-space model of minimal McMillan Degree such that its first N expansion coefficients match the given ones is addressed and solved. For the solution use is made of the properties of the Hambo operator transform theory. The resulting realization algorithms can be applied in an exact and approximative sense and can also be applied to solve a related interpolation problem.
T Q Nguyen - One of the best experts on this subject based on the ideXlab platform.
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generalized block lifting factorization of m channel biorthogonal filter banks for lossy to lossless image coding
IEEE Transactions on Image Processing, 2012Co-Authors: Taizo Suzuki, Masaaki Ikehara, T Q NguyenAbstract:Generalized block-lifting factorization of M-channel (M >; 2) biorthogonal filter banks (BOFBs) for lossy-to-lossless image coding is presented in this paper. Since the proposed block-lifting structure is more general than the conventional lifting factorizations and does NOT require many restrictions such as paraunitary, number of channels, and McMillan Degree in each building block unlike the conventional lifting factorizations, its coding gain is higher than that of the previous methods. Several proposed BOFBs are designed and applied to image coding. Comparing the results with conventional lossy-to-lossless image coding structures, including the 5/3- and 9/7-tap discrete wavelet transforms in JPEG 2000 and a 4 × 8 hierarchical lapped biorthogonal transform in JPEG XR, the proposed BOFBs achieve better result in both objective measure and perceptual visual quality for the images with a lot of high-frequency components.
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block lifting factorization of m channel biorthogonal filter banks with an arbitrary McMillan Degree
International Conference on Image Processing, 2011Co-Authors: Taizo Suzuki, Masaaki Ikehara, T Q NguyenAbstract:A block-lifting factorization of M-channel biorthogonal filter banks (BOFBs) with Degree-N building blocks and even/odd M (M ≥ 2) for lossless-to-lossy image coding is introduced in this paper. In the previous work, block-lifting factorization of M-channel BOFBs has been proposed. Since the block-lifting structure does not require the restriction of determinant of each building block, it achieves better coding performance than the conventional methods. However, the factorization is not completed because McMillan Degree in each building block is fixed M/2 (M is even). This paper proposes a block-lifting factorization without restrictions for a fixed Degree and even block size. Our proposal is validated by several filter designs and their application to lossless-to-lossy image coding.
T.j. De Hoog - One of the best experts on this subject based on the ideXlab platform.
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minimal partial realization from generalized orthonormal basis function expansions
Automatica, 2002Co-Authors: T.j. De Hoog, Z Szabo, Peter S.c. Heuberger, József BokorAbstract:A solution is presented for the problem of realizing a discrete-time LTI state-space model of minimal McMillan Degree such that its first N expansion coefficients in terms of generalized orthonormal basis match a given sequence. The basis considered, also known as the Hambo basis, can be viewed as a generalization of the more familiar Laguerre and two-parameter Kautz constructions, allowing general dynamic information to be incorporated in the basis. For the solution of the problem use is made of the properties of the Hambo operator transform theory that underlies the basis function expansion. As corollary results compact expressions are found by which the Hambo transform and its inverse can be computed efficiently. The resulting realization algorithms can be applied in an approximative sense, for instance, for computing a low-order model from a large basis function expansion that is obtained in an identification experiment.
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Minimal partial realization from orthonormal basis function expansions
Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228), 2001Co-Authors: Peter S.c. Heuberger, Z Szabo, T.j. De Hoog, József BokorAbstract:Given an expansion of a dynamical system in terms of a generalized orthonormal (Hambo) basis, the problem of realizing a state-space model of minimal McMillan Degree such that its first N expansion coefficients match the given ones is addressed and solved. For the solution use is made of the properties of the Hambo operator transform theory. The resulting realization algorithms can be applied in an exact and approximative sense and can also be applied to solve a related interpolation problem.
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minimal partial realization from orthonormal basis function expansions thpll 6
2001Co-Authors: Peter S.c. Heuberger, Z Szab, T.j. De Hoog, J BokortAbstract:Given an expansion of a dynamical system in terms of a generalized orthonormal (Hambo) basis, the problem of realizing a state-space model of minimal McMillan Degree such that its first N expansion coefficients match the given ones is addressed and solved. For the solution use is made of the properties of the Hambo operator transform theory. The resulting realization algorithms can be applied in an exact and approximative sense and can also be applied to solve a related interpolation problem.
Peter S.c. Heuberger - One of the best experts on this subject based on the ideXlab platform.
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minimal partial realization from generalized orthonormal basis function expansions
Automatica, 2002Co-Authors: T.j. De Hoog, Z Szabo, Peter S.c. Heuberger, József BokorAbstract:A solution is presented for the problem of realizing a discrete-time LTI state-space model of minimal McMillan Degree such that its first N expansion coefficients in terms of generalized orthonormal basis match a given sequence. The basis considered, also known as the Hambo basis, can be viewed as a generalization of the more familiar Laguerre and two-parameter Kautz constructions, allowing general dynamic information to be incorporated in the basis. For the solution of the problem use is made of the properties of the Hambo operator transform theory that underlies the basis function expansion. As corollary results compact expressions are found by which the Hambo transform and its inverse can be computed efficiently. The resulting realization algorithms can be applied in an approximative sense, for instance, for computing a low-order model from a large basis function expansion that is obtained in an identification experiment.
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Minimal partial realization from orthonormal basis function expansions
Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228), 2001Co-Authors: Peter S.c. Heuberger, Z Szabo, T.j. De Hoog, József BokorAbstract:Given an expansion of a dynamical system in terms of a generalized orthonormal (Hambo) basis, the problem of realizing a state-space model of minimal McMillan Degree such that its first N expansion coefficients match the given ones is addressed and solved. For the solution use is made of the properties of the Hambo operator transform theory. The resulting realization algorithms can be applied in an exact and approximative sense and can also be applied to solve a related interpolation problem.
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minimal partial realization from orthonormal basis function expansions thpll 6
2001Co-Authors: Peter S.c. Heuberger, Z Szab, T.j. De Hoog, J BokortAbstract:Given an expansion of a dynamical system in terms of a generalized orthonormal (Hambo) basis, the problem of realizing a state-space model of minimal McMillan Degree such that its first N expansion coefficients match the given ones is addressed and solved. For the solution use is made of the properties of the Hambo operator transform theory. The resulting realization algorithms can be applied in an exact and approximative sense and can also be applied to solve a related interpolation problem.
Z Szabo - One of the best experts on this subject based on the ideXlab platform.
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minimal partial realization from generalized orthonormal basis function expansions
Automatica, 2002Co-Authors: T.j. De Hoog, Z Szabo, Peter S.c. Heuberger, József BokorAbstract:A solution is presented for the problem of realizing a discrete-time LTI state-space model of minimal McMillan Degree such that its first N expansion coefficients in terms of generalized orthonormal basis match a given sequence. The basis considered, also known as the Hambo basis, can be viewed as a generalization of the more familiar Laguerre and two-parameter Kautz constructions, allowing general dynamic information to be incorporated in the basis. For the solution of the problem use is made of the properties of the Hambo operator transform theory that underlies the basis function expansion. As corollary results compact expressions are found by which the Hambo transform and its inverse can be computed efficiently. The resulting realization algorithms can be applied in an approximative sense, for instance, for computing a low-order model from a large basis function expansion that is obtained in an identification experiment.
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Minimal partial realization from orthonormal basis function expansions
Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228), 2001Co-Authors: Peter S.c. Heuberger, Z Szabo, T.j. De Hoog, József BokorAbstract:Given an expansion of a dynamical system in terms of a generalized orthonormal (Hambo) basis, the problem of realizing a state-space model of minimal McMillan Degree such that its first N expansion coefficients match the given ones is addressed and solved. For the solution use is made of the properties of the Hambo operator transform theory. The resulting realization algorithms can be applied in an exact and approximative sense and can also be applied to solve a related interpolation problem.