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Docking with PIPER and refinement with SDU in rounds 6-11 of CAPRI

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS 2007年第4期69卷 734-742页

作者： Shen, Yang Brenke, Ryan Kozakov, Dima Comeau, Stephen R. Beglov, Dmitri Vajda, Sandor Boston Univ Dept Biomed Engn Boston MA 02215 USA Boston Univ BioMol Engn Res Ctr Boston MA 02215 USA Boston Univ Program Syst Engn Boston MA 02215 USA Boston Univ Program Bioinformat Boston MA 02215 USA Dyax Corp Boston MA USA

Our approach to protein-protein docking includes three main steps. First we run PIPER, a new rigid body docking program. PIPER is based on the Fast Fourier Transform (FFT) correlation approach that has been extended to use pairwise interactions potentials, thereby substantially increasing the number of near-native structures generated. The interaction potential is also new, based on the DARS (Decoys As the Reference State) principle. In the second step, the 1000 best energy conformations are clustered, and the 30 largest clusters are retained for refinement. Third, the conformations are refined by a new medium-range optimization method SDU (Semi-Definite programming based Underestimation). SDU has been developed to locate global minima within regions of the conformational space in which the energy function is funnel-like. The method constructs a convex quadratic underestimator function based on a set of local energy minima, and uses this function to guide future sampling. The combined method performed reliably without the direct use of biological information in most CAPRI problems that did not require homology modeling, providing acceptable predictions for targets 21, and medium quality predictions for targets 25 and 26.

关键词： fast Fourier transform clustering energy funnel protein docking by PIPER refinement by SDU global optimization semidefinite programming DARS pairwise potential

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Convexity Results on Derivative of Negative Fisher Information Along Heat Flow

Convexity Results on Derivative of Negative Fisher Informati...

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IEEE (first ITW conference of the year) Information Theory Workshop (ITW)

作者： Ken Chen Yanlin Geng School of Telecommunications Engineering Xidian University Xi'an China State Key Laboratory of ISN Xidian University Xi'an China

ISBN: (数字)9798350348934

ISBN: (纸本)9798350348941

Recently, it was shown that the Fisher information is log-convex along the heat flow. The main tools involved were the Cauchy-Schwarz inequality and clever observations on the sum of squares. In this work, we reformulate their method as a rank-one constrained semidefinite programming problem. Then we show that the rank-one matrix can be determined through investigating the first diagonal entry. We apply this new approach to recover existing results, as well as to obtain new results on the derivative of the negative Fisher information along the heat flow: the derivative is convex if it is raised to the power of three-eighths, and is log-convex if the input distribution is log-concave.

关键词： semidefinite programming Conferences Linear matrix inequalities Heat recovery Information theory

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Multibeam Beamforming Design in RIS-aided SISO Communications Subject to Reradiation Masks – Optimization and Machine Learning Methods

Multibeam Beamforming Design in RIS-aided SISO Communication...

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International Symposium on Wireless Communication Systems (ISWCS)

作者： Shumin Wang Marco Di Renzo Marios Poulakis CentraléSupelec Laboratoire des Signaux et Systèmes Université Paris-Saclay CNRS Gif-sur-Yvette France Huawei Technologies Sweden AB Kista Sweden

ISBN: (数字)9798350362510

ISBN: (纸本)9798350362527

Reconfigurable intelligent surfaces (RISs) are considered as one of the most promising technologies to reduce the power consumption and improve the spectral efficiency in future wireless systems. In this paper, we investigate the design of a two-user RIS-aided single-input single-output communication system and propose a beamforming design for RIS optimization, which accounts for specified reradiation masks at the design stage. First, we formulate a max-min optimization problem that aims to maximize the minimum of the normalized powers received at the two users, and we solve it by using semidefinite programming. Then, we devise an efficient implementation of the proposed algorithm based on neural networks. The obtained simulation results show that the proposed schemes are capable of shaping the desired dual-beam radiation pattern towards the directions of interest, while fulfilling the imposed reradiation masks towards other directions. The implementation based on neural networks is shown to reduce the execution time.

关键词： Wireless communication semidefinite programming Power demand Array signal processing Spectral efficiency Simulation Neural networks

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Sparsity-promoting optimal control of consensus and synchronization networks

Sparsity-promoting optimal control of consensus and synchron...

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American Control Conference

作者： Xiaofan Wu Mihailo R. Jovanovic Department of Electrical and Computer Engineering University of Minnesota Minneapolis MN 55455

ISBN: (纸本)9781479932757

We study a class of optimal control problems that are encountered in consensus and synchronization networks. These are characterized by structural constraints that arise from the lack of the absolute measurements for a part of the state vector. In order to deal with these constraints, we introduce a coordinate transformation to eliminate the average mode and assure stabilizability and detectability of the remaining modes. To design networks with low communication requirements, we seek solutions to the l_1 regularized version of the standard H_2 optimal control problem. Such solutions trade off network performance and sparsity of the controller. We also identify a class of optimal control problems that can be cast as semidefinite programs. Examples from power systems and consensus networks are provided to illustrate our developments.

关键词： Alternating direction method of multipliers consensus power systems semidefinite programming sparsity-promoting optimal control synchronization wide-area control Optimal control power systems Coordinate transformations Network absolute measurement terminal area control

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Performance of noisy Nesterov's accelerated method for strongly convex optimization problems

Performance of noisy Nesterov's accelerated method for stron...

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American Control Conference

作者： Hesameddin Mohammadi Meisam Razaviyayn Mihailo R. Jovanovic Department of Electrical and Computer Engineering University of Southern California Los Angeles CA 90089

ISBN: (纸本)9781538679012;9781538679265

We study the performance of noisy gradient descent and Nesterov's accelerated methods for strongly convex objective functions with Lipschitz continuous gradients. The steady-state second-order moment of the error in the iterates is analyzed when the gradient is perturbed by an additive white noise with zero mean and identity covariance. For any given condition number κ, we derive explicit upper bounds on noise amplification that only depend on κ and the problem size. We use quadratic objective functions to derive lower bounds and to demonstrate that the upper bounds are tight up to a constant factor. The established upper bound for Nesterov's accelerated method is larger than the upper bound for gradient descent by a factor of √κ. This gap identifies a fundamental tradeoff that comes with acceleration in the presence of stochastic uncertainties in the gradient evaluation.

关键词： Accelerated first-order algorithms control for optimization convex optimization integral quadratic constraints linear matrix inequalities Nesterov's method noise amplification second-order moments semidefinite programming Upper bound linear matrix inequalities second moment Convex function control optimization Objective function Additive white noise zero mean descent Gradient

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Robust Hybrid Beamforming Design for mmWave Massive MIMO Systems with Imperfect CSI

Robust Hybrid Beamforming Design for mmWave Massive MIMO Sys...

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IEEE Conference on Vehicular Technology (VTC)

作者： Fangyong Peng Yan Yang School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

A robust hybrid beamforming algorithm for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems with imperfect channel state information (CSI) is presented. The imperfect CSI is modeled as a norm ball/bounded model assuming that the actual channel lies within the neighborhood of the estimated channel, leading to the worst-case robust design. In particular, we first utilize the S-procedure to transform the non-convex problem with uncertain CSI into an easily solvable convex semidefinite programming (SDP) problem, thereby obtaining the optimal unconstrained beamformer. Then, we derive the hybrid beamformer that approximates the optimal one by alternating optimization. In this step, the non-convex problem arising from the constant modulus constraints is addressed by the successive convex approximation (SCA). Numerical simulations validate the theoretical analysis and demonstrate that the proposed algorithm is robust to imperfect CSI.

关键词： Vehicular and wireless technologies semidefinite programming Array signal processing Millimeter wave technology Channel estimation Transforms Massive MIMO

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Distributed dynamic state estimation considering renewable generation and packet losses

Distributed dynamic state estimation considering renewable g...

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International Conference on Control, Automation, Robotics and Vision

作者： Md Masud Rana Li Li Steven W. Su Faculty of Engineering and Information Technology University of Technology Sydney Broadway NSW 2007 Australia

ISBN: (纸本)9781509035502

The penetration of renewable distributed energy resources such as wind turbine has been dramatically integrated in distribution networks due to clean, sustainable, and economical green energy. Due to intermittent wind speed, the power generation patterns vary which can risk the distribution network operation. So, it is intrinsically required to monitor the wind turbines in a distributed way. This paper presents an adaptive-then-combine distributed dynamic approach for monitoring the grid under lossy communication link between the wind turbines and energy management system. Firstly, the wind turbine is represented by a state-space linear equation, with sensors deployed to obtain system state information. Based on the mean squared error principle, an adaptive approach is proposed to estimate the local state information. The global estimation is designed by combining estimation results with weighting factors which are calculated by minimizing estimation error covariance based on semi-definite programming. Finally, the convergence analysis indicates that estimation error is gradually decreased, so the estimated state converges to the actual state. The efficacy of the developed approach is verified using the turbine model. The research is valuable for green energy technologies, households and interconnected industrial information societies, and also provides the knowledge towards a smart and secure green energy future.

关键词： wind turbine Adaptive-then-combine Kalman filter Lyapunov function packet losses semidefinite programming

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A Min-Max Approximation-Based SDP Approach to Robust Vehicle Location Estimation in VANETS

A Min-Max Approximation-Based SDP Approach to Robust Vehicle...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Tan-Jan Ho Hua-Yu Luo Dept. of Electrical Engineering Chung Yuan Christian University Taoyuan City Taiwan R.O.C.

ISBN: (数字)9798350370997

ISBN: (纸本)9798350371000

In this paper, we consider robust vehicle localization in a vehicular ad-hoc network (VANET) under changing vehicle velocities and probabilistically mixed line-of-sight (LOS)/non-LOS (NLOS) conditions, where NLOS error statistics and occurrence probabilities are unknown. To tackle the problem, we develop two localization algorithms based on a proposed min-max approximation (MMA)-based semidefinite programming (SDP) method and a proposed advanced measurement preprocessing (AMP) scheme. The AMP method is used for reducing the NLOS influence on raw range measurements received by multiple base stations. Accordingly, we have AMP-MMA and AMP-Joint MMA algorithms. The latter can perform better than the former because it additionally incorporates a neighbor-assisting localization scheme. Simulations show that the two proposed location estimation algorithms perform satisfactorily and outperform the MMA and some tracking algorithms in the literature.

关键词： Location awareness semidefinite programming Error analysis Vehicular ad hoc networks Estimation Line-of-sight propagation programming

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Robust Joint Beamforming and Artificial Noise Design for Secure AF Relay Networks

Robust Joint Beamforming and Artificial Noise Design for Sec...

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IEEE/CIC International Conference on Communications in China

作者： Chao Wang Hui-Ming Wang School of Electronic and Information Engineering Xi'an Jiaotong University

ISBN: (纸本)9781479941452

This letter studies the secure cooperative transmission for an amplify-and-forward (AF) relay network in the presence of multiple multi-antenna eavesdroppers. Since the perfect channel state information (CSI) of the eavesdroppers are not available, we propose a robust joint distributed beamforming and artificial noise scheme to maximize the worst-case secrecy rate of the network, under the total power constraint of all the relay nodes. With the semidefinite relaxation (SDR) technique, the design can be solved by a one-dimension search which involves a sequence of semidefinite programming (SDP). Simulation results demonstrate the validity of the proposed strategy.

关键词： amplify and forward communication array signal processing cooperative communication mathematical programming relay networks (telecommunication) SDP amplify-and-forward relay network multiple multi-antenna eavesdroppers perfect channel state information robust joint beamforming and artificial noise design secure AF relay networks secure cooperative transmission semidefinite programming semidefinite relaxation technique total power constraint Antennas Array signal processing Joints Optimization Relay networks (telecommunications) Robustness

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Large-scale sensor network localization via rigid subnetwork registration

Large-scale sensor network localization via rigid subnetwork...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： K. N. Chaudhury Y. Khoo A. Singer Dept. of Electr. Eng. Indian Inst. of Sci. Bangalore India

ISBN: (纸本)9781467369985

In this paper, we describe an algorithm for sensor network localization (SNL) that proceeds by dividing the whole network into smaller subnetworks, then localizes them in parallel using some fast and accurate algorithm, and finally registers the localized subnetworks in a global coordinate system. We demonstrate that this divide-and-conquer algorithm can be used to leverage existing high-precision SNL algorithms to large-scale networks, which could otherwise only be applied to small-to-medium sized networks. The main contribution of this paper concerns the final registration phase. In particular, we consider a least-squares formulation of the registration problem (both with and without anchor constraints) and demonstrate how this otherwise non-convex problem can be relaxed into a tractable convex program. We provide some preliminary simulation results for large-scale SNL demonstrating that the proposed registration algorithm (together with an accurate localization scheme) offers a good tradeoff between run time and accuracy.

关键词： anchors divide-and-conquer rigid registration scalability semidefinite programming sensor network localization Boat anchors Sensor networks Scalability Divide and conquer Sandia National Laboratories Registration Coordinate system Subnetwork Leverage

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