The Experts below are selected from a list of 69564 Experts worldwide ranked by ideXlab platform
Zhengguo Tan - One of the best experts on this subject based on the ideXlab platform.
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dynamic water fat separation and inhomogeneity mapping Joint Estimation using undersampled triple echo multi spoke radial flash
Magnetic Resonance in Medicine, 2019Co-Authors: Zhengguo Tan, Dirk Voit, Jost M Kollmeier, Martin Uecker, Jens FrahmAbstract:Purpose To achieve dynamic water/fat separation and B 0 field inhomogeneity mapping via model-based reconstructions of undersampled triple-echo multi-spoke radial FLASH acquisitions. Methods This work introduces an undersampled triple-echo multi-spoke radial FLASH sequence, which uses (i) complementary radial spokes per echo train for faster spatial encoding, (ii) asymmetric echoes for flexible and nonuniform echo spacing, and (iii) a golden angle increment across frames for optimal k-space coverage. Joint Estimation of water, fat, B 0 inhomogeneity, and coil sensitivity maps from undersampled triple-echo data poses a nonlinear and non-convex inverse problem which is solved by a model-based reconstruction with suitable regularization. The developed methods are validated using phantom experiments with different degrees of undersampling. Real-time MRI studies of the knee, liver, and heart are conducted without prospective gating or retrospective data sorting at temporal resolutions of 70, 158, and 40 ms, respectively. Results Up to 18-fold undersampling is achieved in this work. Even in the presence of rapid physiological motion, large B 0 field inhomogeneities, and phase wrapping, the model-based reconstruction yields reliably separated water/fat maps in conjunction with spatially smooth inhomogeneity maps. Conclusions The combination of a triple-echo acquisition and Joint reconstruction technique provides a practical solution to time-resolved and motion robust water/fat separation at high spatial and temporal resolution.
Jens Frahm - One of the best experts on this subject based on the ideXlab platform.
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dynamic water fat separation and inhomogeneity mapping Joint Estimation using undersampled triple echo multi spoke radial flash
Magnetic Resonance in Medicine, 2019Co-Authors: Zhengguo Tan, Dirk Voit, Jost M Kollmeier, Martin Uecker, Jens FrahmAbstract:Purpose To achieve dynamic water/fat separation and B 0 field inhomogeneity mapping via model-based reconstructions of undersampled triple-echo multi-spoke radial FLASH acquisitions. Methods This work introduces an undersampled triple-echo multi-spoke radial FLASH sequence, which uses (i) complementary radial spokes per echo train for faster spatial encoding, (ii) asymmetric echoes for flexible and nonuniform echo spacing, and (iii) a golden angle increment across frames for optimal k-space coverage. Joint Estimation of water, fat, B 0 inhomogeneity, and coil sensitivity maps from undersampled triple-echo data poses a nonlinear and non-convex inverse problem which is solved by a model-based reconstruction with suitable regularization. The developed methods are validated using phantom experiments with different degrees of undersampling. Real-time MRI studies of the knee, liver, and heart are conducted without prospective gating or retrospective data sorting at temporal resolutions of 70, 158, and 40 ms, respectively. Results Up to 18-fold undersampling is achieved in this work. Even in the presence of rapid physiological motion, large B 0 field inhomogeneities, and phase wrapping, the model-based reconstruction yields reliably separated water/fat maps in conjunction with spatially smooth inhomogeneity maps. Conclusions The combination of a triple-echo acquisition and Joint reconstruction technique provides a practical solution to time-resolved and motion robust water/fat separation at high spatial and temporal resolution.
See-may Phoong - One of the best experts on this subject based on the ideXlab platform.
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a time domain Joint Estimation algorithm for cfo and i q imbalance in wideband direct conversion receivers
IEEE Transactions on Wireless Communications, 2012Co-Authors: See-may PhoongAbstract:Carrier frequency offset (CFO) and in-phase and quadrature-phase (I/Q) imbalance are two of the common front-end impairments in low-cost communication devices. It is known that CFO can cause significant performance degradation in multi-carrier modulation (MCM) systems. Also, the existence of the I/Q imbalance usually reduces the accuracy of CFO Estimation. In this paper, we propose a new data-aided scheme for the Joint Estimation of CFO and I/Q imbalance using simple matrix formulation. The proposed algorithms utilize only the periodicity of the generalized periodic pilot (GPP). They do not need to know the channel impulse response and the exact values of the training sequence. Moreover, our method has a low complexity and its performance compares favorably with the existing methods.
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Joint Estimation of i q imbalance cfo and channel response for mimo ofdm systems
IEEE Transactions on Communications, 2010Co-Authors: Yuan-hwui Chung, See-may PhoongAbstract:In this paper, we study the Joint Estimation of inphase and quadrature-phase (I/Q) imbalance, carrier frequency offset (CFO), and channel response for multiple-input multipleoutput (MIMO) orthogonal frequency division multiplexing (OFDM) systems using training sequences. A new concept called channel residual energy (CRE) is introduced. We show that by minimizing the CRE, we can Jointly estimate the I/Q imbalance and CFO without knowing the channel response. The proposed method needs only one OFDM block for training and the training symbols can be arbitrary. Moreover when the training block consists of two repeated sequences, a low complexity two-step approach is proposed to solve the Joint Estimation problem. Simulation results show that the mean-squared error (MSE) of the proposed method is close to the Cramer-Rao bound (CRB).
Jacob Stromberg - One of the best experts on this subject based on the ideXlab platform.
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time changed levy libor market model pricing and Joint Estimation of the cap surface and swaption cube
Journal of Financial Economics, 2014Co-Authors: Markus Leippold, Jacob StrombergAbstract:We propose a novel time-changed Levy LIBOR (London Interbank Offered Rate) market model for Jointly pricing of caps and swaptions. The time changes are split into three components. The first component allows matching the volatility term structure, the second generates stochastic volatility, and the third accommodates for stochastic skew. The parsimonious model is flexible enough to accommodate the behavior of both caps and swaptions. For the Joint Estimation we use a comprehensive data set spanning the financial crisis of 2007–2010. We find that, even during this period, neither market is as fragmented as suggested by the previous literature.
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time changed levy libor market model pricing and Joint Estimation of the cap surface and swaption cube
Social Science Research Network, 2013Co-Authors: Markus Leippold, Jacob StrombergAbstract:We propose a novel time-changed Levy LIBOR market model for the Joint pricing of caps and swaptions. The time changes are split into three components. The first component allows us to match the volatility term structure, the second generates stochastic volatility, and the third one accommodates for stochastic skew. The model is parsimonious, yet flexible enough to accommodate the behavior of both caps and swaptions well. For the Joint Estimation we use a comprehensive dataset spanning the recent financial crisis. We fi nd that, even during the recent fi nancial crisis, neither market is as fragmented as suggested by the previous literature.
S. M. Sameer - One of the best experts on this subject based on the ideXlab platform.
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Iterative Joint carrier frequency offset and doubly selective channel Estimation in high-mobility MIMO-OFDMA uplink using oblique projection
IEEE Transactions on Vehicular Technology, 2016Co-Authors: P. Muneer, S. M. SameerAbstract:In this paper, we propose a novel pilot aided Joint Estimation technique for carrier frequency offset (CFO) and doubly selective (both time and frequency selective) channel (DSC) in high-mobility multiple-input–multiple-output orthogonal frequency-division multiple-access (MIMO-OFDMA) uplink systems. As the maximum-likelihood (ML) solution to this Estimation problem is highly computationally tedious due to the requirement of multidimensional optimization, we propose an iterative scheme based on the oblique projection (OP), which separates the user signal in each iteration, resulting in decomposition of highly complex multidimensional search to many 1-D searches. We also derive a low-complexity approximation to the proposed technique, which makes use of precalculated projection matrices stored at the base station. The exact Cramer–Rao bound (CRB) of the Joint Estimation of CFOs and DSCs in MIMO-OFDMA uplink is also derived. Simulation studies indicate that the mean square error performance of the proposed techniques nearly achieves the CRB even at low signal-to-noise ratios (SNRs).
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pilot aided Joint Estimation of doubly selective channel and carrier frequency offsets in ofdma uplink with high mobility users
IEEE Transactions on Vehicular Technology, 2015Co-Authors: P. Muneer, S. M. SameerAbstract:In this paper, we propose a novel pilot-aided Joint channel and carrier frequency offset (CFO) Estimation method for orthogonal frequency-division multiple access (OFDMA) uplink systems with users operating in time- and frequency-selective (doubly selective) fading environments. We use Bernstein basis polynomials (BBPs) to capture rapid time variations of the channel, which avoids the identifiability issue in estimating large number of actual channel coefficients. We make use of space-alternating generalized expectation–maximization maximum a posteriori probability (SAGE-MAP) algorithm for the Joint Estimation of CFOs and channel coefficients. The convergence properties of the proposed method is assessed and proved analytically. The exact Bayesian Cramer–Rao bound (BCRB) for the MAP Estimation problem is also derived and is shown to be comparable to the mean squared error (MSE) of the proposed technique.
