The Experts below are selected from a list of 112392 Experts worldwide ranked by ideXlab platform
Chong Meng Samson See - One of the best experts on this subject based on the ideXlab platform.
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robust minimum ell_ 1 norm adaptive beamformer against intermittent sensor failure and steering Vector Error
IEEE Transactions on Antennas and Propagation, 2010Co-Authors: Ying Zhang, Joni Polili Lie, Chong Meng Samson SeeAbstract:A robust adaptive beamformer is described to mitigate against steering Vector Error and intermittent sensor(s) failure which exists in the form of impulsive noise in the received signal of failed sensor(s). This new beamformer iteratively minimizes the l 1 -norm of the beamformer's output, subject to a prespecified set of quadratic constraints which target on attenuating the influence caused by steering Vector Error. To solve the proposed optimization problem, gradient descent algorithm is adopted. The choice of the Lagrange multiplier ? as well as the adaptive step-size ?(k) are derived in detail. Simulation results verify validity and advantages of the proposed algorithms over some existing methods.
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Robust Minimum $\ell_{1}$ -Norm Adaptive Beamformer Against Intermittent Sensor Failure and Steering Vector Error
IEEE Transactions on Antennas and Propagation, 2010Co-Authors: Ying Zhang, Joni Polili Lie, Chong Meng Samson SeeAbstract:A robust adaptive beamformer is described to mitigate against steering Vector Error and intermittent sensor(s) failure which exists in the form of impulsive noise in the received signal of failed sensor(s). This new beamformer iteratively minimizes the l 1 -norm of the beamformer's output, subject to a prespecified set of quadratic constraints which target on attenuating the influence caused by steering Vector Error. To solve the proposed optimization problem, gradient descent algorithm is adopted. The choice of the Lagrange multiplier ? as well as the adaptive step-size ?(k) are derived in detail. Simulation results verify validity and advantages of the proposed algorithms over some existing methods.
Ying Zhang - One of the best experts on this subject based on the ideXlab platform.
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robust minimum ell_ 1 norm adaptive beamformer against intermittent sensor failure and steering Vector Error
IEEE Transactions on Antennas and Propagation, 2010Co-Authors: Ying Zhang, Joni Polili Lie, Chong Meng Samson SeeAbstract:A robust adaptive beamformer is described to mitigate against steering Vector Error and intermittent sensor(s) failure which exists in the form of impulsive noise in the received signal of failed sensor(s). This new beamformer iteratively minimizes the l 1 -norm of the beamformer's output, subject to a prespecified set of quadratic constraints which target on attenuating the influence caused by steering Vector Error. To solve the proposed optimization problem, gradient descent algorithm is adopted. The choice of the Lagrange multiplier ? as well as the adaptive step-size ?(k) are derived in detail. Simulation results verify validity and advantages of the proposed algorithms over some existing methods.
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Robust Minimum $\ell_{1}$ -Norm Adaptive Beamformer Against Intermittent Sensor Failure and Steering Vector Error
IEEE Transactions on Antennas and Propagation, 2010Co-Authors: Ying Zhang, Joni Polili Lie, Chong Meng Samson SeeAbstract:A robust adaptive beamformer is described to mitigate against steering Vector Error and intermittent sensor(s) failure which exists in the form of impulsive noise in the received signal of failed sensor(s). This new beamformer iteratively minimizes the l 1 -norm of the beamformer's output, subject to a prespecified set of quadratic constraints which target on attenuating the influence caused by steering Vector Error. To solve the proposed optimization problem, gradient descent algorithm is adopted. The choice of the Lagrange multiplier ? as well as the adaptive step-size ?(k) are derived in detail. Simulation results verify validity and advantages of the proposed algorithms over some existing methods.
Zhigang Fan - One of the best experts on this subject based on the ideXlab platform.
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Color Imaging: Processing, Hardcopy, and Applications - Analysis of color Error diffusion with Vector Error filters
Color Imaging XI: Processing Hardcopy and Applications, 2006Co-Authors: Zhigang FanAbstract:As Vector Error filters are capable of passing Errors generated in one color component to other color components, it provides more flexibility in shaping the halftone texture. As a result, it may potentially produce halftones with better image quality. In this paper, we analyze color Error diffusion with Vector Error filters. In particular, we will discuss its halftone spectrum features and its stability conditions with respect to the filter coefficients. For spectrum analysis, we will derive the high-pass and average color preservation conditions, which ensure decent image quality. Since Error diffusion is a feedback system, the Vector Error filters may cause instability, if it is not properly designed. This may potentially generate ever-increasing quantization Error that masks the input and produces unacceptable output images. The stability conditions we will discuss provide guidelines for designing stable systems.
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Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts - Semi-Vector Error diffusion for color images
1999Co-Authors: Zhigang Fan, Steven J. HarringtonAbstract:Color Error diffusion can be classified into two types, namely, Vector Error diffusion and scalar Error diffusion, according to the underlying quantization methods. Compared to scalar Error diffusion, Vector Error diffusion is superior in image quality. However, it requires significantly more computation, and can introduce artifacts due to accumulation of the Errors in output device space. In this paper, we propose a new quantization algorithm for CMY color Error diffusion. The algorithm, which we call semi-Vector quantization, has a low computational complexity and a high stability as similar to scalar Error diffusion, but yields superb quality images close to those generated from Vector Error diffusion.
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Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts - Boundary artifacts reduction in Vector Error diffusion
1999Co-Authors: Zhigang FanAbstract:Color Error diffusion can be classified into two types, namely, Vector Error diffusion and scalar Error diffusion, according to the underlying quantization methods. Compared to scalar Error diffusion, Vector Error diffusion is typically superior in overall image quality. However, it may occasionally introduce boundary artifacts. A color band, at a width of a few pixels to tens of pixels may appear along the edges. The artifacts are referred in literature to slow response for leading edges and smear for trailing edges, respectively. In this paper, we present a simple yet effective method for reducing the boundary artifacts.
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Semi-Vector Error diffusion for color images
Color Imaging: Device-Independent Color Color Hardcopy and Graphic Arts IV, 1998Co-Authors: Zhigang Fan, Steven J. HarringtonAbstract:Color Error diffusion can be classified into two types, namely, Vector Error diffusion and scalar Error diffusion, according to the underlying quantization methods. Compared to scalar Error diffusion, Vector Error diffusion is superior in image quality. However, it requires significantly more computation, and can introduce artifacts due to accumulation of the Errors in output device space. In this paper, we propose a new quantization algorithm for CMY color Error diffusion. The algorithm, which we call semi- Vector quantization, has a low computational complexity and a high stability as similar to scalar Error diffusion, but yields superb quality images close to those generated from Vector Error diffusion.
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Boundary artifacts reduction in Vector Error diffusion
Color Imaging: Device-Independent Color Color Hardcopy and Graphic Arts IV, 1998Co-Authors: Zhigang FanAbstract:Color Error diffusion can be classified into two types, namely, Vector Error diffusion and scalar Error diffusion, according to the underlying quantization methods. Compared to scalar Error diffusion, Vector Error diffusion is typically superior in overall image quality. However, it may occasionally introduce boundary artifacts. A color band, at a width of a few pixels to tens of pixels may appear along the edges. The artifacts are referred in literature to slow response for leading edges and smear for trailing edges, respectively. In this paper, we present a simple yet effective method for reducing the boundary artifacts.
Joni Polili Lie - One of the best experts on this subject based on the ideXlab platform.
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robust minimum ell_ 1 norm adaptive beamformer against intermittent sensor failure and steering Vector Error
IEEE Transactions on Antennas and Propagation, 2010Co-Authors: Ying Zhang, Joni Polili Lie, Chong Meng Samson SeeAbstract:A robust adaptive beamformer is described to mitigate against steering Vector Error and intermittent sensor(s) failure which exists in the form of impulsive noise in the received signal of failed sensor(s). This new beamformer iteratively minimizes the l 1 -norm of the beamformer's output, subject to a prespecified set of quadratic constraints which target on attenuating the influence caused by steering Vector Error. To solve the proposed optimization problem, gradient descent algorithm is adopted. The choice of the Lagrange multiplier ? as well as the adaptive step-size ?(k) are derived in detail. Simulation results verify validity and advantages of the proposed algorithms over some existing methods.
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Robust Minimum $\ell_{1}$ -Norm Adaptive Beamformer Against Intermittent Sensor Failure and Steering Vector Error
IEEE Transactions on Antennas and Propagation, 2010Co-Authors: Ying Zhang, Joni Polili Lie, Chong Meng Samson SeeAbstract:A robust adaptive beamformer is described to mitigate against steering Vector Error and intermittent sensor(s) failure which exists in the form of impulsive noise in the received signal of failed sensor(s). This new beamformer iteratively minimizes the l 1 -norm of the beamformer's output, subject to a prespecified set of quadratic constraints which target on attenuating the influence caused by steering Vector Error. To solve the proposed optimization problem, gradient descent algorithm is adopted. The choice of the Lagrange multiplier ? as well as the adaptive step-size ?(k) are derived in detail. Simulation results verify validity and advantages of the proposed algorithms over some existing methods.
Steven J. Harrington - One of the best experts on this subject based on the ideXlab platform.
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Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts - Semi-Vector Error diffusion for color images
1999Co-Authors: Zhigang Fan, Steven J. HarringtonAbstract:Color Error diffusion can be classified into two types, namely, Vector Error diffusion and scalar Error diffusion, according to the underlying quantization methods. Compared to scalar Error diffusion, Vector Error diffusion is superior in image quality. However, it requires significantly more computation, and can introduce artifacts due to accumulation of the Errors in output device space. In this paper, we propose a new quantization algorithm for CMY color Error diffusion. The algorithm, which we call semi-Vector quantization, has a low computational complexity and a high stability as similar to scalar Error diffusion, but yields superb quality images close to those generated from Vector Error diffusion.
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Semi-Vector Error diffusion for color images
electronic imaging, 1998Co-Authors: Steven J. HarringtonAbstract:Color Error diffusion can be classified into two types, namely, Vector Error diffusion and scalar Error diffusion, according to the underlying quantization methods. Compared to scalar Error diffusion, Vector Error diffusion is superior in image quality. However, it requires significantly more computation, and can introduce artifacts due to accumulation of the Errors in output device space. In this paper, we propose a new quantization algorithm for CMY color Error diffusion. The algorithm, which we call semi- Vector quantization, has a low computational complexity and a high stability as similar to scalar Error diffusion, but yields superb quality images close to those generated from Vector Error diffusion.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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Semi-Vector Error diffusion for color images
Color Imaging: Device-Independent Color Color Hardcopy and Graphic Arts IV, 1998Co-Authors: Zhigang Fan, Steven J. HarringtonAbstract:Color Error diffusion can be classified into two types, namely, Vector Error diffusion and scalar Error diffusion, according to the underlying quantization methods. Compared to scalar Error diffusion, Vector Error diffusion is superior in image quality. However, it requires significantly more computation, and can introduce artifacts due to accumulation of the Errors in output device space. In this paper, we propose a new quantization algorithm for CMY color Error diffusion. The algorithm, which we call semi- Vector quantization, has a low computational complexity and a high stability as similar to scalar Error diffusion, but yields superb quality images close to those generated from Vector Error diffusion.
