The Experts below are selected from a list of 177 Experts worldwide ranked by ideXlab platform
Bin Wang - One of the best experts on this subject based on the ideXlab platform.
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polygonal approximation using Integer particle swarm optimization
Information Sciences, 2014Co-Authors: Xiaozheng Zhang, Douglas Brown, Bin Wang, Hanxi LiAbstract:Polygonal approximation is an effective yet challenging digital curve representation for image analysis, pattern recognition and computer vision. This paper proposes a novel approach, Integer particle swarm optimization (iPSO), for polygonal approximation. When compared to the traditional binary version of particle swarm optimization (bPSO), the new iPSO directly uses an Integer Vector to represent the candidate solution and provides a more efficient and convenient means for solution processing. The velocity and position updating mechanisms in iPSO not only have clear physical meaning, but also guarantee the optimality of the solutions. The method is suitable for polygonal approximation which could otherwise be an intractable optimization problem. The proposed method has been tested on commonly used synthesized shapes and lake contours extracted from the maps of four famous lakes in the world. The experimental results show that the proposed iPSO has better solution quality and computational efficiency than the bPSO-based methods and better solution quality than the other state-of-the-art methods.
Jinming Wen - One of the best experts on this subject based on the ideXlab platform.
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closed form word error rate analysis for successive interference cancellation decoders
IEEE Transactions on Wireless Communications, 2018Co-Authors: Jinming Wen, Chintha Tellambura, Pingzhi FanAbstract:We consider the detection of an Integer Vector ${\hat { {{x}}}}\in \mathbb {Z}^{n}$ from the linear observation ${{y}}= {A} {\hat { {{x}}}} + {v}$ , where ${A}\in \mathbb {R}^{m\times n}$ is a random matrix with independent and identically distributed (i.i.d.) standard Gaussian $\mathcal {N}(0,1)$ entries, and ${v}\in \mathbb {R}^{m}$ is a noise Vector with i.i.d. $\mathcal {N}(0,\sigma ^{2})$ entries with given $\sigma $ . In digital communications, ${\hat { {{x}}}}$ is typically uniformly distributed over an $n$ -dimensional box $\mathcal {B}$ . For this detection problem, successive interference cancellation decoders are popular due to their low complexity, and a detailed analysis of their word error rates (WERs) is highly useful. In this paper, we derive closed-form WER expressions for two cases: (1) ${\hat { {{x}}}}\in \mathbb {Z}^{n}$ is fixed and (2) ${\hat { {{x}}}}$ is uniformly distributed over $\mathcal {B}$ . We also investigate some of their properties in detail and show that they agree closely with simulated word error probabilities.
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closed form word error rate analysis for successive interference cancellation decoders
arXiv: Information Theory, 2018Co-Authors: Jinming Wen, Chintha Tellambura, Pingzhi FanAbstract:We consider the estimation of an Integer Vector $\hbx\in \mathbb{Z}^n$ from the linear observation $\y=\A\hbx+\v$, where $\A\in\mathbb{R}^{m\times n}$ is a random matrix with independent and identically distributed (i.i.d.) standard Gaussian $\mathcal{N}(0,1)$ entries, and $\v\in \mathbb{R}^m$ is a noise Vector with i.i.d. $\mathcal{N}(0,\sigma^2 )$ entries with given $\sigma$. In digital communications, $\hbx$ is typically uniformly distributed over an $n$-dimensional box $\mathcal{B}$. For this estimation problem, successive interference cancellation (SIC) decoders are popular due to their low complexity, and a detailed analysis of their word error rates (WERs) is highly useful. In this paper, we derive closed-form WER expressions for two cases: (1) $\hbx\in \mathbb{Z}^n$ is fixed and (2) $\hbx$ is uniformly distributed over $\mathcal{B}$. We also investigate some of their properties in detail and show that they agree closely with simulated word error probabilities.
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a closed form symbol error rate analysis for successive interference cancellation decoders
International Conference on Communications, 2017Co-Authors: Jinming Wen, Chintha TellamburaAbstract:Wireless and digital communications applications require the detection of an Integer Vector x from y = Ax + v, where A ∊ Rm×n is a random matrix whose entries are independent and identically distributed (i.i.d.) standard Gaussian N(0,1) entries, and v ∊ Rm is a noise Vector following the Gaussian distribution N(0,σ2) with given σ. The successive interference cancellation (SIC) decoders are frequently used to detect X due to their high accuracy and low implementation complexity. However, to accurately characterize their performance, we need to analyze their symbol error rates (SER). In this paper, we derive a closed-form expression for the SER of the SIC decoders and investigate its properties. Simulated error probabilities of the SIC decoders agree closely with our theoretical expressions.
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success probability of the babai estimators for box constrained Integer linear models
IEEE Transactions on Information Theory, 2017Co-Authors: Jinming Wen, Xiao-wen ChangAbstract:In many applications including communications, one may encounter a linear model where the parameter Vector $\hat { {x}}$ is an Integer Vector in a box. To estimate $\hat { {x}}$ , a typical method is to solve a box-constrained Integer least squares problem. However, due to its high complexity, the box-constrained Babai Integer point $ {x}^ {\scriptscriptstyle \text {BB}}$ is commonly used as a suboptimal solution. In this paper, we first derive formulas for the success probability $P^ {\scriptscriptstyle \text {BB}}$ of $ {x}^ {\scriptscriptstyle \text {BB}}$ and the success probability $P^ {\scriptscriptstyle \text {OB}}$ of the ordinary Babai Integer point $ {x}^ {\scriptscriptstyle \text {OB}}$ when $\hat { {x}}$ is uniformly distributed over the constraint box. Some properties of $P^ {\scriptscriptstyle \text {BB}}$ and $P^ {\scriptscriptstyle \text {OB}}$ and the relationship between them are studied. Then, we investigate the effects of some column permutation strategies on $ {P}^ {\scriptscriptstyle \text {BB}}$ . In addition to V-BLAST and SQRD, we also consider the permutation strategy involved in the LLL lattice reduction, to be referred to as LLL-P. On the one hand, we show that when the noise is relatively small, LLL-P always increases $P^ {\scriptscriptstyle \text {BB}}$ and argue why both V-BLAST and SQRD often increase $P^ {\scriptscriptstyle \text {BB}}$ ; and on the other hand, we show that when the noise is relatively large, LLL-P always decreases $P^ {\scriptscriptstyle \text {BB}}$ and argue why both V-BLAST and SQRD often decrease $P^ {\scriptscriptstyle \text {BB}}$ . We also derive a column permutation invariant bound on $P^ {\scriptscriptstyle \text {BB}}$ , which is an upper bound and a lower bound under these two opposite conditions, respectively. Numerical results demonstrate our findings. Finally, we consider a conjecture concerning $ {x}^ {\scriptscriptstyle \text {OB}}$ proposed by Ma et al. We first construct an example to show that the conjecture does not hold in general, and then show that it does hold under some conditions.
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success probability of the babai estimators for box constrained Integer linear models
arXiv: Information Theory, 2014Co-Authors: Jinming Wen, Xiao-wen ChangAbstract:In many applications including communications, one may encounter a linear model where the parameter Vector $\hbx$ is an Integer Vector in a box. To estimate $\hbx$, a typical method is to solve a box-constrained Integer least squares (BILS) problem. However, due to its high complexity, the box-constrained Babai Integer point $\x^\sBB$ is commonly used as a suboptimal solution. In this paper, we first derive formulas for the success probability $P^\sBB$ of $\x^\sBB$ and the success probability $P^\sOB$ of the ordinary Babai Integer point $\x^\sOB$ when $\hbx$ is uniformly distributed over the constraint box. Some properties of $P^\sBB$ and $P^\sOB$ and the relationship between them are studied. Then, we investigate the effects of some column permutation strategies on $\P^\sBB$. In addition to V-BLAST and SQRD, we also consider the permutation strategy involved in the LLL lattice reduction, to be referred to as LLL-P. On the one hand, we show that when the noise is relatively small, LLL-P always increases $P^\sBB$ and argue why both V-BLAST and SQRD often increase $P^\sBB$; and on the other hand, we show that when the noise is relatively large, LLL-P always decreases $P^\sBB$ and argue why both V-BLAST and SQRD often decrease $P^\sBB$. We also derive a column permutation invariant bound on $P^\sBB$, which is an upper bound and a lower bound under these two opposite conditions, respectively. Numerical results demonstrate our findings. Finally, we consider a conjecture concerning $\x^\sOB$ proposed by Ma et al. We first construct an example to show that the conjecture does not hold in general, and then show that it does hold under some conditions.
Hanxi Li - One of the best experts on this subject based on the ideXlab platform.
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polygonal approximation using Integer particle swarm optimization
Information Sciences, 2014Co-Authors: Xiaozheng Zhang, Douglas Brown, Bin Wang, Hanxi LiAbstract:Polygonal approximation is an effective yet challenging digital curve representation for image analysis, pattern recognition and computer vision. This paper proposes a novel approach, Integer particle swarm optimization (iPSO), for polygonal approximation. When compared to the traditional binary version of particle swarm optimization (bPSO), the new iPSO directly uses an Integer Vector to represent the candidate solution and provides a more efficient and convenient means for solution processing. The velocity and position updating mechanisms in iPSO not only have clear physical meaning, but also guarantee the optimality of the solutions. The method is suitable for polygonal approximation which could otherwise be an intractable optimization problem. The proposed method has been tested on commonly used synthesized shapes and lake contours extracted from the maps of four famous lakes in the world. The experimental results show that the proposed iPSO has better solution quality and computational efficiency than the bPSO-based methods and better solution quality than the other state-of-the-art methods.
Pingzhi Fan - One of the best experts on this subject based on the ideXlab platform.
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closed form word error rate analysis for successive interference cancellation decoders
IEEE Transactions on Wireless Communications, 2018Co-Authors: Jinming Wen, Chintha Tellambura, Pingzhi FanAbstract:We consider the detection of an Integer Vector ${\hat { {{x}}}}\in \mathbb {Z}^{n}$ from the linear observation ${{y}}= {A} {\hat { {{x}}}} + {v}$ , where ${A}\in \mathbb {R}^{m\times n}$ is a random matrix with independent and identically distributed (i.i.d.) standard Gaussian $\mathcal {N}(0,1)$ entries, and ${v}\in \mathbb {R}^{m}$ is a noise Vector with i.i.d. $\mathcal {N}(0,\sigma ^{2})$ entries with given $\sigma $ . In digital communications, ${\hat { {{x}}}}$ is typically uniformly distributed over an $n$ -dimensional box $\mathcal {B}$ . For this detection problem, successive interference cancellation decoders are popular due to their low complexity, and a detailed analysis of their word error rates (WERs) is highly useful. In this paper, we derive closed-form WER expressions for two cases: (1) ${\hat { {{x}}}}\in \mathbb {Z}^{n}$ is fixed and (2) ${\hat { {{x}}}}$ is uniformly distributed over $\mathcal {B}$ . We also investigate some of their properties in detail and show that they agree closely with simulated word error probabilities.
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closed form word error rate analysis for successive interference cancellation decoders
arXiv: Information Theory, 2018Co-Authors: Jinming Wen, Chintha Tellambura, Pingzhi FanAbstract:We consider the estimation of an Integer Vector $\hbx\in \mathbb{Z}^n$ from the linear observation $\y=\A\hbx+\v$, where $\A\in\mathbb{R}^{m\times n}$ is a random matrix with independent and identically distributed (i.i.d.) standard Gaussian $\mathcal{N}(0,1)$ entries, and $\v\in \mathbb{R}^m$ is a noise Vector with i.i.d. $\mathcal{N}(0,\sigma^2 )$ entries with given $\sigma$. In digital communications, $\hbx$ is typically uniformly distributed over an $n$-dimensional box $\mathcal{B}$. For this estimation problem, successive interference cancellation (SIC) decoders are popular due to their low complexity, and a detailed analysis of their word error rates (WERs) is highly useful. In this paper, we derive closed-form WER expressions for two cases: (1) $\hbx\in \mathbb{Z}^n$ is fixed and (2) $\hbx$ is uniformly distributed over $\mathcal{B}$. We also investigate some of their properties in detail and show that they agree closely with simulated word error probabilities.
Simon Halfon - One of the best experts on this subject based on the ideXlab platform.
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Integer Vector addition systems with states
International Workshop on Reachability Problems, 2014Co-Authors: Christoph Haase, Simon HalfonAbstract:This paper studies reachability, coverability and inclusion problems for Integer Vector Addition Systems with States (ℤ-VASS) and extensions and restrictions thereof. A ℤ-VASS comprises a finite-state controller with a finite number of counters ranging over the Integers. Although it is folklore that reachability in ℤ-VASS is NP-complete, it turns out that despite their naturalness, from a complexity point of view this class has received little attention in the literature. We fill this gap by providing an in-depth analysis of the computational complexity of the aforementioned decision problems. Most interestingly, it turns out that while the addition of reset operations to ordinary VASS leads to undecidability and Ackermann-hardness of reachability and coverability, respectively, they can be added to ℤ-VASS while retaining NP-completeness of both coverability and reachability.
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Integer Vector addition systems
2014Co-Authors: Christoph Haase, Simon HalfonAbstract:This paper studies reachability, coverability and inclusion problems for Integer Vector Addition Systems with States (ZVASS) and extensions and restrictions thereof. A ZVASS comprises a finite-state controller with a finite number of counters ranging over the Integers. Although it is folklore that reachability in ZVASS is NP-complete, it turns out that despite their naturalness, from a complexity point of view this class has received little attention in the literature. We fill this gap by providing an in-depth analysis of the computational complexity of the aforementioned decision problems. Most interestingly, it turns out that while the addition of reset operations to ordinary VASS leads to undecidability and Ackermann-hardness of reachability and coverability, respectively, they can be added to ZVASS while retaining NP-completness of both coverability and reachability.
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Integer Vector Addition Systems with States
Lecture Notes in Computer Science, 2014Co-Authors: Christoph Haase, Simon HalfonAbstract:This paper studies reachability, coverability and inclusion problems for Integer Vector Addition Systems with States (ZVASS) and extensions and restrictions thereof. A ZVASS comprises a finite-state controller with a finite number of counters ranging over the Integers. Although it is folklore that reachability in ZVASS is NP-complete, it turns out that despite their naturalness, from a complexity point of view this class has received little attention in the literature. We fill this gap by providing an in-depth analysis of the computational complexity of the aforementioned decision problems. Most interestingly, it turns out that while the addition of reset operations to ordinary VASS leads to undecidability and Ackermann-hardness of reachability and coverability, respectively, they can be added to ZVASS while retaining NP-completness of both coverability and reachability.