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globally optimal algorithm for Design of 0.7 T Actively Shielded Whole-Body Open MRI Superconducting Magnet System

IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY 2013年第3期23卷 4401104页

作者： Ni, Zhipeng Hu, Geli Li, Lankai Yu, Gongqi Wang, Qiuliang Yan, Luguang Chinese Acad Sci Key Lab Appl Superconduct Inst Elect Engn Beijing 100190 Peoples R China Sichuan Univ Chengdu 610065 Sichuan Peoples R China

A 0.7-T open magnetic resonance imaging superconducting magnet system with actively shielded technique was designed and will be fabricated. The design methodology of the open structure magnetic resonance superconducting magnet is employed by a hybrid optimization strategy with combination with linear programming and nonlinear optimization algorithm. The linear programming was employed to search the coils' initial position and shape with advantage of high efficient and global optimization, and the nonlinear optimization algorithm was to discrete the initial data into solenoids to reach the system requirements, such as field strength and homogeneity over an interesting region, the scope of 5 Gauss fringe field, maximum magnetic field and maximum hoop stress within solenoids. The hybrid optimization is flexible and efficient to design conventional cylindrical system and split open system.

关键词： Actively shielded globally optimal algorithm open magnetic resonance imaging (MRI) superconducting magnet whole-body

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globally optimal Design of a Distributed Scalar Quantizer for Linear Classification

Globally Optimal Design of a Distributed Scalar Quantizer fo...

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IEEE International Symposium on Information Theory (ISIT)

作者： Dumitrescu, Sorina Zendehboodi, Sara McMaster Univ Dept Elect & Comp Engn Hamilton ON Canada

ISBN: (纸本)9781538682098

This work is concerned with the design of a distributed scalar quantizer (DSQ) with two encoders, for linear classification. The objective of the optimization is to minimize the classification error of the classifier applied to the quantized inputs in the training sequence with respect to the classifier applied on unquantized inputs. We prove that the optimal DSQ design problem is equivalent to a minimum weight path problem with some constraints on the number and types of edges in a certain weighted directed acyclic graph. Further, we propose a solution algorithm with time complexity O(K1K2N4), where N is the size of the training sequence while K-1 and K-2 are the numbers of cells of the two encoders, respectively. In addition, we develop faster design algorithms for the equal-rate case (i.e., K-1 = K-2 = K). Specifically, when the training sequence is symmetric, we prove that there exists an optimal DSQ where the thresholds of the encoders' partitions are interleaved. By leveraging this property and the symmetry of the training sequence, we propose a O(KN2) time solution algorithm. For the case when the training sequence is not symmetric, we propose an algorithm with the same time complexity that minimizes an upper bound on the misclassification ratio. Experimental results prove the considerable superiority of the proposed approaches in comparison with prior work in both symmetric and asymmetric scenarios.

关键词： Distributed scalar quantizer linear classification globally optimal algorithm minimum weight path problem

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Design of Successively Refinable Unrestricted Polar Quantizer

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IEEE TRANSACTIONS ON COMMUNICATIONS 2019年第5期67卷 3525-3539页

作者： Wu, Huihui Dunntrescu, Sorina McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4K1 Canada Columbia Univ Dept Elect Engn New York NY 10027 USA

This paper addresses the design of two-stage successively refinable unrestricted polar quantizers for bivariate circularly symmetric sources in the entropy-constrained and fixed-rate cases. The proposed solutions are globally optimal when the thresholds of the magnitude quantizers are confined to finite discretizations of the interval [0, infinity). The algorithm developed for the entropy-constrained case involves a series of stages, including solving the minimum-weight path problem for multiple node pairs in certain weighted directed acyclic graphs. The asymptotical time complexity is O((K1K2Pmax)-P-2), where K-1 and K-2 are the sizes of the sets of possible magnitude thresholds of the coarse and refined unrestricted polar quantizers (UPQs), respectively, while P-max is an upper bound on the number of phase levels in any phase quantizer of the coarse UPQ. The solution algorithm for the fixed-rate case is based on solving a succession of dynamic programming problems for multiple coarse quantizer bins. The time complexity in the fixed-rate case amounts to O((K1K2NN1)-N-2), where N-1 is the number of cells of the coarse UPQ and N is the ratio between the number of bins of the fine and coarse UPQs. The extensive experimental results on a bivariate circularly symmetric Gaussian source show the effectiveness of the proposed schemes.

关键词： Unrestricted polar quantization successively refinable quantizer globally optimal algorithm minimum-weight path problem dynamic programming Monge property

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optimal Design of a Two-Stage Wyner-Ziv Scalar Quantizer With Forwardly/Reversely Degraded Side Information

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IEEE TRANSACTIONS ON COMMUNICATIONS 2019年第2期67卷 1437-1451页

作者： Zheng, Qixue Dumitrescu, Sorina McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4L8 Canada

This paper addresses the optimal design of a two-stage Wyner-Ziv scalar quantizer with forwardly or reversely degraded side information (SI) for finite-alphabet sources and SI. We assume that the binning is performed optimally and address the design of the quantizer partitions. The optimization problem is formulated as the minimization of a weighted sum of distortions and rates. The proposed solution is globally optimal when the cells in each partition are contiguous. The solution algorithm is based on solving the single-source or the all-pairs minimum-weight path (MWP) problem in certain weighted directed acyclic graphs. When the conventional dynamic programming technique is used to solve the underlying MWP problems, the time complexity achieved is O(N-3), where N is the size of the source alphabet. A so-called partial Monge property is additionally introduced, and a faster solution algorithm exploiting this property is proposed. Experimental results assess the practical performance of the proposed scheme.

关键词： Wyner-Ziv coding degraded side information scalar quantization globally optimal algorithm minimum-weight path problem Monge property

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Design of optimal Entropy-Constrained Unrestricted Polar Quantizer for Bivariate Circularly Symmetric Sources

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IEEE TRANSACTIONS ON COMMUNICATIONS 2018年第5期66卷 2169-2180页

作者： Wu, Huihui Dumitrescu, Sorina McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4L8 Canada

This paper proposes an algorithm for the design of entropy-constrained unrestricted polar quantizer (ECUPQ) for bivariate circularly symmetric sources. The algorithm is globally optimal for the class of ECUPQs with magnitude quantizer thresholds confined to a finite set. The optimization problem is formulated as the minimization of a weighted sum of distortion and entropy, and the proposed solution is based on modeling the problem as a minimum-weight path problem in a certain weighted directed acyclic graph. Each graph edge corresponds to a possible magnitude quantizer bin and computing its weight involves solving another optimization problem. We develop a fast strategy for evaluating all edge weights, leading to a O(K-2 + KPmax) time solution algorithm, where K is the size of the set of possible magnitude thresholds and P-max is the maximum number of phase levels. The practical performance of the proposed algorithm is assessed for a bivariate circularly symmetric Gaussian source, at rates ranging from 0.5 to 6 bits/sample. Our results demonstrate that the proposed approach achieves performance very close to the asymptotically optimal ECUPQ at all rates, while at low rates it significantly outperforms all previous UPQ schemes. Notably, peak improvement of 0.755 dB can be achieved for rates below 2.5.

关键词： Unrestricted polar quantization entropy-constrained quantizer globally optimal algorithm minimum-weight path problem

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Design of optimal Scalar Quantizer for Sequential Coding of Correlated Sources

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IEEE TRANSACTIONS ON COMMUNICATIONS 2019年第1期67卷 693-707页

作者： Wu, Huihui Dumitrescu, Sorina McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4L8 Canada

This paper addresses the design of a sequential scalar quantizer (SSQ) for finite-alphabet correlated sources in the fixed-rate (FR) and entropy-constrained (EC) cases. The optimization problem is formulated as the minimization of a weighted sum of distortions and rates. The proposed solution is globally optimal for the class of SSQs with convex cells and is based on solving the minimum-weight path (MWP) problem in the EC case, respectively, a length-constrained MWP problem in the FR case, in a series of weighted directed acyclic graphs. The asymptotic time complexity is O((K1K22)-K-2), where K-1 and K-2 are the respective sizes of the alphabets of the two sources. Additionally, it is proved that, by applying the proposed algorithms to discretizations of correlated sources with continuous joint probability density function, the performance approaches that of the optimal EC-SSQ, respectively, FR-SSQ, with convex cells for the original sources as the accuracy of the discretization increases. Extensive experiments performed with correlated Gaussian sources validate the effectiveness in practice of the proposed approach in approximating the optimal SSQ for the case of continuous-alphabet sources.

关键词： Sequential coding scalar quantization globally optimal algorithm minimum-weight path problem

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Design of General Entropy-Constrained Successively Refinable Unrestricted Polar Quantizer

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IEEE TRANSACTIONS ON COMMUNICATIONS 2020年第6期68卷 3369-3385页

作者： Wu, Huihui Dumitrescu, Sorina McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4K1 Canada McMaster Univ Dept Elect & Comp Engn Hamilton ON H3A 0E9 Canada

This paper presents an algorithm for the optimal design of general entropy-constrained successively refinable unrestricted polar quantizer, i.e., with arbitrary number L of refinement levels, for bivariate circularly symmetric sources. The optimization problem is formulated as the minimization of a weighted sum of distortions and entropies for the scenario where the magnitude quantizers' thresholds are confined to a predefined finite set. The proposed solution algorithm is globally optimal. It involves L stages, where each stage corresponds to an unrestricted polar quantizer (UPQ) level, and includes solving the minimum-weight path problem for multiple node pairs in a series of weighted directed acyclic graphs. Additionally, we derive an upper bound P-max((l)), l is an element of [1 : L], on the possible number of phase levels in any phase quantizer of the l-th level UPQ, which grows linearly with l. The time complexity of the proposed approach is O((LK3)-K-2 P-max((1))), where K is the cardinality of the predefined set of possible magnitude thresholds. Finally, the experimental results for L = 3 demonstrate the effectiveness in practice of the proposed scheme.

关键词： Successively refinable quantizer entropyconstrained unrestricted polar quantization globally optimal algorithm minimum-weight path problem

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Design of optimal Fixed-Rate Unrestricted Polar Quantizer for Bivariate Circularly Symmetric Sources

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IEEE SIGNAL PROCESSING LETTERS 2018年第5期25卷 715-719页

作者： Wu, Huihui Dumitrescu, Sorina McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4L8 Canada

This letter presents an algorithm for the design of fixed-rate unrestricted polar quantizer (FUPQ) for bivariate circularly symmetric sources. The proposed algorithm is globally optimal for the class of FUPQs with the magnitude quantizer thresholds restricted to some predefined finite set. The solution algorithm is based on dynamic programming, which is further accelerated by exploiting the monotonicity property of the cost function. The time complexity of the accelerated algorithm is O(K N-2), where N is the number of target qunatizer levels and K is the size of the predefined set of possible thresholds. The experimental results show that our approach outperforms the previous tractable designs when the total number of quantizer levels ranges between 25 and 256.

关键词： Dynamic programming fixed-rate quantizer globally optimal algorithm unrestricted polar quantization

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optimal Design of A Two-stage Wyner-Ziv Scalar Quantizer with Degraded Side Information 29

Optimal Design of A Two-stage Wyner-Ziv Scalar Quantizer wit...

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29th Biennial Symposium on Communications

作者： Zheng, Qixue Dumitrescu, Sorina

ISBN: (纸本)9781538657355

This work addresses the optimal design of a twostage Wyner-Ziv scalar quantizer with degraded side information (SI). We assume that binning is performed optimally and address the design of the nested quantizer partitions. The optimization problem is formulated as minimizing a weighted sum of distortions and rates. The proposed solution algorithm is globally optimal when the source and SI are discrete, while the partition cells are contiguous. The algorithm is based on solving the single source or the all-pairs minimum-weight path problem in certain weighted directed acyclic graphs. A so-called partial Monge property is additionally introduced and a faster solution algorithm exploiting this property is proposed. Experimental results assess the practical performance of the proposed scheme.

关键词： Wyner-Ziv coding scalar quantization globally optimal algorithm minimum-weight path Monge property

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Design of optimal Entropy-constrained Scalar Quantizer for Sequential Coding of Correlated Sources

Design of Optimal Entropy-constrained Scalar Quantizer for S...

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2017 IEEE Information Theory Workshop (ITW)

作者： Wu, Huihui Dumitrescu, Sorina McMaster Univ Dept Elect & Comp Engn Hamilton ON Canada

ISBN: (纸本)9781509030972

This work addresses the design of a sequential code for correlated sources using entropy-constrained scalar quantization at each encoder. We consider discrete sources and propose a globally optimal algorithm to minimize a weighted sum of distortions and rates. Our algorithm is based on solving the minimum weight path problem in a series of appropriately constructed weighted directed acyclic graphs. Its asymptotical time complexity is O((N1N22)-N-2), where N-1 and N-2 denote the alphabet sizes of the two sources, respectively.

关键词： Sequential coding scalar quantization entropy-constrained globally optimal algorithm minimum weight path problem

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