检索结果-内蒙古大学图书馆

Joint optimisation convex-negative matrix factorisation for multi-modal image collection summarisation based on images and tags

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IET COMPUTER VISION 2019年第2期13卷 125-130页

作者： Zhang, Wenkai Fu, Kun Sun, Xian Zhang, Yuhang Sun, Hao Wang, Hongqi Chinese Acad Sci Key Lab Spatial Informat Proc & Applicat Syst Tec Inst Elect 19North 4th Ring Rd West Beijing Peoples R China Chinese Acad Sci Inst Elect 19North 4th Ring Rd West Beijing Peoples R China Univ Chinese Acad Sci 19 Yuquan Rd Beijing Peoples R China

Image collection summarisation aims to represent a large-scale multi-modal collection with a small subset of images and tags, helping navigate a large image dataset. Most extant methods leverage the contributions of text-to-visual summaries, ignoring the visual contribution to the textual topic. When the tags are weakly labelled, the textual topic cannot accurately reflect the visual summary. To solve this, the authors propose a novel model, joint optimisation of convex non-negative matrix factorisation, which incorporates images and tags in a beneficial way. The objective function contains visual and textual error functions, sharing the same indicator matrix, connecting different modal relations. Then, they propose an iterative algorithm to optimise the proposed model. Finally, they explore the effects of different visual feature representations (e.g. bag-of-words and deep learning) on multi-modal collection summary. Our proposed method is then compared with state-of-the-art algorithms using two multi-modal datasets (i.e. MIRFlickr and NUS-WIDE-SCENE). Experimental results demonstrate the effectiveness of their proposed approach.

关键词： convex programming matrix decomposition image representation iterative methods joint optimisation convex-negative matrix factorisation multimodal image collection summarisation image dataset text-to-visual summaries objective function textual error functions visual error functions iterative algorithm visual feature representations multimodal collection summary

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Extending BiCG and BiCR methods to solve the Stein tensor equation

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COMPUTERS & MATHEMATICS WITH APPLICATIONS 2019年第12期77卷 3117-3127页

作者： Xu, Xiangjian Wang, Qing-Wen Shanghai Univ Dept Math Shanghai 200444 Peoples R China Nantong Univ Sch Sci Nantong 226019 Jiangsu Peoples R China

The biconjugate gradients (BiCG) and biconjugate residual (BiCR) methods are attractive ways for solving nonsymmetric linear system Ax = b. In this paper, the BiCG and BiCR methods are extended to solve the high order Stein tensor equation. The convergent properties of the developed iterative algorithms are studied. Numerical examples are provided to confirm the theoretical results, which demonstrate that the proposed algorithms are effective and feasible for solving the Stein tensor equation. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Stein tensor equation Biconjugate gradients (BiCG) method Biconjugate residual (BiCR) method iterative algorithm k-mode product

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Generalized Attitude Determination with One Dominant Vector Observation

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2019年第4期42卷 885-893页

作者： Crassidis, John L. Cheng, Yang Univ Buffalo State Univ New York Dept Mech & Aerosp Engn Amherst NY 14260 USA Mississippi State Univ Dept Aerosp Engn Mississippi State MS 39762 USA

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Distributed H∞ consensus control for nonlinear multi-agent systems under switching topologies via relative output feedback

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NEURAL COMPUTING & APPLICATIONS 2019年第1期31卷 1-9页

作者： Jiang, Yulian Wang, Hongquan Wang, Shenquan Changchun Univ Technol Coll Elect & Elect Engn Changchun 130012 Jilin Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

For a class of nonlinear multi-agent systems under switching topologies with disturbances, we propose a distributed H consensus control protocol based on relative output feedback and utilize an iterative algorithm for solving nonlinear matrix inequality in this paper. Firstly, a consensus control protocol via relative output feedback is designed. Then, an iterative algorithm is utilized to calculate nonlinear matrix inequality. By this, the output feedback gain is designed but not chosen, which increases the design degree of freedom and meanwhile H performance index is obtained. Finally, the proposed theory is applied to multiple simple-pendulums network systems driven by DC motors, and simulation results show the effectiveness of the designed consensus control protocol.

关键词： Multi-agent systems Relative output feedback Consensus iterative algorithm

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Optimal power allocation for energy-efficient full-duplex cognitive relay networks under primary interference

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IET COMMUNICATIONS 2019年第19期13卷 3317-3325页

作者： Poornima, S. Babu, A. V. Natl Inst Technol Dept Elect & Commun Engn Calicut Kerala India

This study investigates optimal power allocation (OPA) for maximising the energy efficiency (EE) of dual-hop underlay full-duplex cognitive relay network, under the influence of interference from primary source. The OPA for the EE optimisation is constrained on the maximum transmit power of the secondary nodes and the interference threshold power which can be tolerated at the primary destination. The authors convert the initial non-convex optimisation problem to a concave fractional programming form and propose an iterative algorithm using parametric transformation to find the OPA vector. Further, they prove that the point of convergence of the proposed iterative algorithm is a Karush-Kuhn-Tucker point of the initial non-convex problem. They numerically demonstrate the EE improvement achieved by the proposed algorithms over equal power allocation strategy.

关键词： relay networks (telecommunication) optimisation concave programming cognitive radio energy conservation convex programming iterative methods optimal power allocation energy-efficient full-duplex cognitive relay networks primary interference energy efficiency dual-hop underlay full-duplex cognitive relay network primary source maximum transmit power interference threshold power primary destination nonconvex optimisation problem concave fractional programming form iterative algorithm OPA vector nonconvex problem equal power allocation strategy

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A novel approach for FNLP with piecewise linear membership functions

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CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2019年 191卷 88-95页

作者： Wen, Bo Gu, Wen Yang, Bo Li, Hongguang Chen, Xiaochun Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing Peoples R China Beijing Univ Chem Technol Coll Chem Engn Beijing Peoples R China Changzheng Engn Co Ltd Shanghai Peoples R China

In the fuzzy nonlinear programming (FNLP) domain, piecewise linear membership functions (PLMFs) are often employed to linearize the nonlinear membership functions. However, the linearization error will reduce the accuracy of the solution, which has become an obstacle to the application of PLMFs. In this paper, we present an iterative algorithm based on geometrical means to solve the problems mentioned above. Firstly, the linearization error can be reduced by gradually modifying the programming model. Subsequently, compared with traditional methods, the linearization model is determined only by weighing the linearization degree of membership function and the accuracy of programming results, the proposed method is more directly and effectively. Furthermore, in-depth discussions are also given along with the algorithm for demonstrating the rationality. Finally, the proposed method is validated and compared with other methods. A real example is examined to demonstrate applicability of the proposed method in this paper.

关键词： Fuzzy nonlinear programming Piecewise linear membership functions Error analysis iterative algorithm

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A Fast and Effective Sensitivity Calculation Method for Circuit Input Vectors

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IEEE TRANSACTIONS ON RELIABILITY 2019年第3期68卷 938-953页

作者： Xiao, Jie Lou, Jungang Jiang, Jianhui Zhejiang Univ Technol Coll Comp Sci & Technol Hangzhou 313000 Zhejiang Peoples R China Huzhou Univ Coll Informat Sci Huzhou 313000 Peoples R China Tongji Univ Software Engn Dept Shanghai 200072 Peoples R China

The sensitivity of circuit input vectors plays an important role in estimating circuit reliability bounds and identifying reliability-critical gates. Consequently, to effectively calculate the circuit sensitivity for the input vectors is becoming a necessity for nanocircuits, helping circuit designers to select the architecture that best optimizes the tradeoffs between reliability and area power delay. Combining probability signals and employing the iterative strategy presented inMonte Carlo method, this paper proposes an iterative algorithm based on a probabilistic transfer matrix to investigate the circuit sensitivity for the given input vectors, ensuring computational precision and speed. Simulation results on benchmark circuits show that the proposed algorithm is an efficient and accurate method to calculate the sensitivity of the applied input vectors, and that it can be used to improve circuit reliability at a small cost in the early stages of circuit design.

关键词： Circuit input vectors iterative algorithm probabilistic transfer matrix probability signal reliability improvement sensitivity analysis

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Speckle-reduced holographic beam shaping with modified Gerchberg-Saxton algorithm

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OPTICS COMMUNICATIONS 2019年 433卷 44-51页

作者： Pang, Hui Liu, Wenjing Cao, Axiu Deng, Qiling Chinese Acad Sci Inst Opt & Elect Chengdu 610209 Sichuan Peoples R China

Holographic laser beam shaping using a spatial light modulator can provide flexible adaptation of the intensity profile. However, speckle noise exists in the shaped beams, which reduces the beam quality seriously. In this paper, a new method is proposed to implement noise reduced flat-top beam shaping. The Gerchberg-Saxton (GS) algorithm with special spherical initial phase profile is adopted to calculate the phase-only hologram. When the spherical phase distribution is properly selected, the speckle free flat-top beam with high diffraction efficiency and low root-mean-square error can be obtained. Both simulations and experiments are performed to verify the feasibility of the proposed method. The comparison with the conventional GS algorithm using a random initial phase distribution is also carried out.

关键词： Laser beam shaping Computer holography iterative algorithm

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Robust Secure Beamforming for Multibeam Satellite Communication Systems

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2019年第6期68卷 6202-6206页

作者： Lin, Zhi Lin, Min Ouyang, Jian Zhu, Wei-Ping Panagopoulos, Athanasios D. Alouini, Mohamed-Slim Army Engn Univ PLA Coll Commun Engn Nanjing 210007 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Key Lab Broadband Wireless Commun & Sensor Networ Minist Educ Nanjing 210003 Jiangsu Peoples R China Concordia Univ Dept Elect & Comp Engn Montreal PQ H3G 1M8 Canada Nanjing Univ Posts & Telecommun Sch Commun & Informat Engn Nanjing 210003 Jiangsu Peoples R China Natl Tech Univ Athens Sch Elect & Comp Engn Zografos 15780 Greece King Abdullah Univ Sci & Technol Div Comp Elect & Math Sci & Engn Thuwal 239556900 Saudi Arabia

This paper proposes a robust beamforming (BF) scheme to enhance the physical layer security (PLS) of a multibeam satellite system operating at Ka band. By considering the effects of beam gain, path loss, and rain attenuation, we first formulate a constrained optimization problem to maximize the minimal achievable secrecy rate of multiuser under the assumption of imperfect eavesdropping channel and the constraint of total transmit power on the satellite. Since the problem is non-convex and mathematically intractable, we exploit the sequential convex approximation approach and S-procedure method to transform the original problem into one with a series of linear matrix inequality and second-order cone constraints, and then propose an iterative scheme to obtain the optimal BF weight vectors. Finally, simulation results showing the effectiveness and superiority of the proposed algorithm are provided.

关键词： Multibeam satellite system secrecy rate iterative algorithm sequential convex approximation

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Active Polynomial Chaos Expansion for Reliability-Based Design Optimization

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AIAA JOURNAL 2019年第12期57卷 5431-5446页

作者： Zhou, Yicheng Lu, Zhenzhou Northwestern Polytech Univ Sch Aeronaut POB 120 Xian 710072 Shaanxi Peoples R China

The aim of the present paper is to develop a strategy for solving reliability-based design optimization (RBDO) problems by sparse polynomial chaos expansion (PCE). Because classic sparse regression methods cannot provide the surrogate error measure that can be employed to improve the sampling performance for failure probability estimation in RBDO, Bayesian compressed sensing with state-of-the-art performance is employed to build sparse PCE in the paper. In the meanwhile, a new active learning function is proposed to adaptively select new training points. Two goals can be achieved using this criterion;that is, most of the selected training points are selected from the desired regions to approximate limit state surfaces, and these points tend to be far away from the existing points in the current design to avoid the clustering problem. Because the sparse PCEs are built in an augmented space, it is made numerically affordable to solve the RBDO problem with no extra computational cost. The computation capability of the proposed method is demonstrated by several analytical RBDO problems. Meanwhile, the design optimization of a stiffened rib of the wing edge in a certain aircraft also verifies its good engineering applicability.

关键词： Numerical Stability Cumulative Distribution Function Sequential Quadratic Programming Finite Element Modeling Design of Experiments Mathematical Models Monte Carlo Simulation Support Vector Machine Sensitivity Analysis iterative algorithm

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