The Experts below are selected from a list of 72810 Experts worldwide ranked by ideXlab platform
Douglas L. Jones - One of the best experts on this subject based on the ideXlab platform.
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An adaptive optimal-kernel time-Frequency Representation
IEEE Transactions on Signal Processing, 1995Co-Authors: Douglas L. Jones, Richard G BaraniukAbstract:Time-Frequency Representations with fixed windows or kernels figure prominently in many applications, but perform well only for limited classes of signals. Representations with signal-dependent kernels can overcome this limitation. However, while they often perform well, most existing schemes are block-oriented techniques unsuitable for on-line implementation or for tracking signal components with characteristics that change with time. The time-Frequency Representation developed in the present paper, based on a signal-dependent radially Gaussian kernel that adapts over time, surmounts these difficulties. The method employs a short-time ambiguity function both for kernel optimization and as an intermediate step in computing constant-time slices of the Representation. Careful algorithm design provides reasonably efficient computation and allows on-line implementation. Certain enhancements, such as cone-kernel constraints and approximate retention of marginals, are easily incorporated with little additional computation. While somewhat more expensive than fixed kernel Representations, this new technique often provides much better performance. Several examples illustrate its behavior on synthetic and real-world signals. >
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a signal dependent time Frequency Representation fast algorithm for optimal kernel design
IEEE Transactions on Signal Processing, 1994Co-Authors: Richard G Baraniuk, Douglas L. JonesAbstract:A time-Frequency Representation based on an optimal, signal-dependent kernel has been previously been proposed in an attempt to overcome one of the primary limitations of bilinear time-Frequency distributions: that the best kernel and distribution depend on the signal to be analyzed. The optimization formulation for the signal-dependent kernel results in a linear program with a unique feature: a tree structure that summarizes a set of constraints on the kernel. The authors present a fast algorithm based on sorting to solve a special class of linear programs that includes the problem of interest. For a kernel with Q variables, the running time of the algorithm is O(Q log Q), which is several orders of magnitude less than any other known method for solving this class of linear program. This efficiency enables the computation of the signal-dependent, optimal-kernel time-Frequency Representation at a cost that is on the same order as a fixed-kernel distribution. An important property of the optimal kernel is that it takes on essentially only the values of 1 and 0. >
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ICASSP (4) - An adaptive optimal-kernel time-Frequency Representation
IEEE International Conference on Acoustics Speech and Signal Processing, 1993Co-Authors: Douglas L. Jones, R.g. BariniukAbstract:Signal-dependent time-Frequency Representations perform well for a much wider range of signals than any fixed-kernel distribution. The time-Frequency Representation presented here, based on a signal-dependent radially Gaussian kernel that adapts over time, tracks signal component variations over time and supports online implementation for signals of arbitrary length. The method uses a short-time ambiguity function for kernel optimization and as an intermediate step in computing constant-time slices of the time-Frequency Representation. While somewhat more expensive than fixed-kernel Representation, this technique often provides much better performance. >
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ICASSP - A high resolution data-adaptive time-Frequency Representation
ICASSP '87. IEEE International Conference on Acoustics Speech and Signal Processing, 1Co-Authors: Douglas L. Jones, T.w. ParksAbstract:We present a data-adaptive time-Frequency Representation that obtains high resolution of signal components in time-Frequency. This Representation overcomes the often poor resolution of the traditional short-time Fourier transform, while avoiding the nonlinearities that make the Wigner distribution and other bilinear Representations difficult to interpret and use. The new method uses adaptive Gaussian windows, with the window parameters varying at different time-Frequency locations to maximize the local signal concentration in time-Frequency. Two methods for selecting the Gaussian parameters are presented: a parameter estimation approach, and a method that maximizes a measure of local signal concentration.
B. Faiz - One of the best experts on this subject based on the ideXlab platform.
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determination of the group and phase velocities from time Frequency Representation of wigner ville
Ndt & E International, 1999Co-Authors: Rachid Latif, E Aassif, Gérard Maze, Ali Moudden, B. FaizAbstract:Abstract The experimental measurement of the group and phase velocities of some circumferential waves propagating around a thin elastic tube is a still complex operation. In this study, we show that the dispersion velocity can be determined from a time–Frequency Representation. We use the Wigner–Ville method by virtue of its interesting properties. On some time–Frequency images, the symmetric (S0) and antisymmetric (A1) circumferential waves are identified. The group velocity dispersion estimated from these images is compared with that computed by the proper mode theory method. A good agreement is obtained. The phase velocity is also determined from the group velocity.
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Determination of the group and phase velocities from time–Frequency Representation of Wigner–Ville
NDT & E International, 1999Co-Authors: Rabia Latif, E Aassif, Gérard Maze, Ali Moudden, B. FaizAbstract:Abstract The experimental measurement of the group and phase velocities of some circumferential waves propagating around a thin elastic tube is a still complex operation. In this study, we show that the dispersion velocity can be determined from a time–Frequency Representation. We use the Wigner–Ville method by virtue of its interesting properties. On some time–Frequency images, the symmetric (S0) and antisymmetric (A1) circumferential waves are identified. The group velocity dispersion estimated from these images is compared with that computed by the proper mode theory method. A good agreement is obtained. The phase velocity is also determined from the group velocity.
Richard G Baraniuk - One of the best experts on this subject based on the ideXlab platform.
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An adaptive optimal-kernel time-Frequency Representation
IEEE Transactions on Signal Processing, 1995Co-Authors: Douglas L. Jones, Richard G BaraniukAbstract:Time-Frequency Representations with fixed windows or kernels figure prominently in many applications, but perform well only for limited classes of signals. Representations with signal-dependent kernels can overcome this limitation. However, while they often perform well, most existing schemes are block-oriented techniques unsuitable for on-line implementation or for tracking signal components with characteristics that change with time. The time-Frequency Representation developed in the present paper, based on a signal-dependent radially Gaussian kernel that adapts over time, surmounts these difficulties. The method employs a short-time ambiguity function both for kernel optimization and as an intermediate step in computing constant-time slices of the Representation. Careful algorithm design provides reasonably efficient computation and allows on-line implementation. Certain enhancements, such as cone-kernel constraints and approximate retention of marginals, are easily incorporated with little additional computation. While somewhat more expensive than fixed kernel Representations, this new technique often provides much better performance. Several examples illustrate its behavior on synthetic and real-world signals. >
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a signal dependent time Frequency Representation fast algorithm for optimal kernel design
IEEE Transactions on Signal Processing, 1994Co-Authors: Richard G Baraniuk, Douglas L. JonesAbstract:A time-Frequency Representation based on an optimal, signal-dependent kernel has been previously been proposed in an attempt to overcome one of the primary limitations of bilinear time-Frequency distributions: that the best kernel and distribution depend on the signal to be analyzed. The optimization formulation for the signal-dependent kernel results in a linear program with a unique feature: a tree structure that summarizes a set of constraints on the kernel. The authors present a fast algorithm based on sorting to solve a special class of linear programs that includes the problem of interest. For a kernel with Q variables, the running time of the algorithm is O(Q log Q), which is several orders of magnitude less than any other known method for solving this class of linear program. This efficiency enables the computation of the signal-dependent, optimal-kernel time-Frequency Representation at a cost that is on the same order as a fixed-kernel distribution. An important property of the optimal kernel is that it takes on essentially only the values of 1 and 0. >
E Aassif - One of the best experts on this subject based on the ideXlab platform.
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determination of the group and phase velocities from time Frequency Representation of wigner ville
Ndt & E International, 1999Co-Authors: Rachid Latif, E Aassif, Gérard Maze, Ali Moudden, B. FaizAbstract:Abstract The experimental measurement of the group and phase velocities of some circumferential waves propagating around a thin elastic tube is a still complex operation. In this study, we show that the dispersion velocity can be determined from a time–Frequency Representation. We use the Wigner–Ville method by virtue of its interesting properties. On some time–Frequency images, the symmetric (S0) and antisymmetric (A1) circumferential waves are identified. The group velocity dispersion estimated from these images is compared with that computed by the proper mode theory method. A good agreement is obtained. The phase velocity is also determined from the group velocity.
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Determination of the group and phase velocities from time–Frequency Representation of Wigner–Ville
NDT & E International, 1999Co-Authors: Rabia Latif, E Aassif, Gérard Maze, Ali Moudden, B. FaizAbstract:Abstract The experimental measurement of the group and phase velocities of some circumferential waves propagating around a thin elastic tube is a still complex operation. In this study, we show that the dispersion velocity can be determined from a time–Frequency Representation. We use the Wigner–Ville method by virtue of its interesting properties. On some time–Frequency images, the symmetric (S0) and antisymmetric (A1) circumferential waves are identified. The group velocity dispersion estimated from these images is compared with that computed by the proper mode theory method. A good agreement is obtained. The phase velocity is also determined from the group velocity.
Ali Moudden - One of the best experts on this subject based on the ideXlab platform.
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determination of the group and phase velocities from time Frequency Representation of wigner ville
Ndt & E International, 1999Co-Authors: Rachid Latif, E Aassif, Gérard Maze, Ali Moudden, B. FaizAbstract:Abstract The experimental measurement of the group and phase velocities of some circumferential waves propagating around a thin elastic tube is a still complex operation. In this study, we show that the dispersion velocity can be determined from a time–Frequency Representation. We use the Wigner–Ville method by virtue of its interesting properties. On some time–Frequency images, the symmetric (S0) and antisymmetric (A1) circumferential waves are identified. The group velocity dispersion estimated from these images is compared with that computed by the proper mode theory method. A good agreement is obtained. The phase velocity is also determined from the group velocity.
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Determination of the group and phase velocities from time–Frequency Representation of Wigner–Ville
NDT & E International, 1999Co-Authors: Rabia Latif, E Aassif, Gérard Maze, Ali Moudden, B. FaizAbstract:Abstract The experimental measurement of the group and phase velocities of some circumferential waves propagating around a thin elastic tube is a still complex operation. In this study, we show that the dispersion velocity can be determined from a time–Frequency Representation. We use the Wigner–Ville method by virtue of its interesting properties. On some time–Frequency images, the symmetric (S0) and antisymmetric (A1) circumferential waves are identified. The group velocity dispersion estimated from these images is compared with that computed by the proper mode theory method. A good agreement is obtained. The phase velocity is also determined from the group velocity.
