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Node-Wise Scheduling Algorithm of ADMM Decoding Based on Line Segment projection

IEEE COMMUNICATIONS LETTERS 2022年第4期26卷 738-742页

作者： Xia, Qiaoqiao He, Pinquan Wang, Xin Liu, Huiyang Zhang, Qinglin Cent China Normal Univ Coll Phys Sci & Technol Wuhan 430072 Peoples R China

In order to simplify the node-wise scheduling algorithm of the alternating direction method of multipliers (NS-ADMM) decoding, approximate line segment projection algorithm (LSA) is adopted to perform the projection in the node-wise scheduling algorithm. Experimental results show that using approximate line segment projection instead of precise projection in node-wise scheduling algorithm will yield a poor frame error rate (FER) performance. To solve this problem, dynamic scheduling strategy that selects the message-passing schedule according to the convergence status of the check node is proposed. Simulation results demonstrate that the modified node-wise scheduling algorithm based on line segment projection outperforms existing decoding algorithms in terms of FER performance and convergence speed, while it has good error correction performance with a lower computational complexity.

关键词： Decoding Convergence Scheduling algorithms projection algorithms Approximation algorithms Schedules Dynamic scheduling Alternating direction method of multipliers (ADMM) low-density parity-check (LDPC) codes check polytope projection message scheduling

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A multichannel affine projection algorithm with applications to multichannel acoustic echo cancellation

引用

IEEE SIGNAL PROCESSING LETTERS 1996年第2期3卷 35-37页

作者： Benesty, J Duhamel, P Grenier, Y ENST/SIG

A straightforward generalization of the so-called affine projection algorithm (APA) to the multichannel (MC) case is easily obtained. However, due to the strong correlation between the input signals of the various channels, the resulting algorithm converges very slowly. This letter describes the way to overcome this problem and derives an efficient algorithm that turns out to make use of additional orthogonal projections.

关键词： projection algorithms Acoustic applications Microphones Echo cancellers Least squares approximation Jacobian matrices Teleconferencing MPEG 4 Standard Degradation Stochastic processes

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Robust state estimation based on projection statistics (vol 11, pg 216, 1996)

引用

IEEE TRANSACTIONS ON POWER SYSTEMS 1996年第2期11卷 1118-+页

作者： Mili, L Cheniae, MG Vichare, NS Rousseeuw, PJ UNIV INSTELLING ANTWERP DEPT MATH B-2610 ANTWERP BELGIUM

This paper describes a fast and robust method for identifying the leverage points of a linearized power system state estimation model. These are measurements whose projections on the space spanned by the row vectors of the weighted Jacobian matrix, the so-called factor space, do not follow the pattern of the bulk of the point cloud. In other words, their projections are outliers in the factor space. The proposed method is implemented through a new version of the projection algorithm that accounts for the sparsity of the Jacobian matrix. It assigns to each data point a projection statistic defined as the maximum of the standardized projections of the point cloud on some directions passing through the origin. Based on these projection statistics, a robustly weighted Schweppe-type GM-estimator is defined, which can be computed by a reweighted least squares algorithm, The computational efficiency and the robustness of the method are demonstrated on the IEEE-14 bus and the 118-bus systems.

关键词： Robustness State estimation Statistics Power system modeling Jacobian matrices Clouds Power system measurements projection algorithms Least squares methods Computational efficiency

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BACK projection SPEED IMPROVEMENT FOR 3-D RECONSTRUCTION

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 1977年第5期24卷 1999-2005页

作者： KWOH, YS REED, IS TRUONG, TK UNIV SO CALIF DEPT ELECT ENGNLOS ANGELESCA 90027 CALTECH JET PROP LABPASADENACA 91103

The Fourier convolution algorithm has been used to reconstruct a 3-D density function. The method involves a particular choice of weighting function to convolve with projection data sets scanned through various angles from 0 to π. The convolved data are then back projected to obtain a 2-D image. A 3-D reconstruction is obtained as a stack of 2-D images. Because the new tomographic machines have much finer resolution, the number or projection data to be processed is considerably more than with the early models. The amount of data to be processed makes critical the need for improvements in both the speed as well as the accuracy. A first step toward speed improvement is to use a finite field transform to perform the convolutions. This was shown previously by the authors to be, in fact, a worthwhile effort. Another and most time-consuming part of the reconstruction algorithm is the so-called back-projection algorithm. The purpose of this paper is to present a method for speeding-up the back-projection algorithm by cutting down the computational time by a factor of two.

关键词： Three dimensional displays Filters Image reconstruction Frequency response Convolution Contracts Galois fields Propulsion Laboratories projection algorithms

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Widely Linear Maximum Complex Correntropy Criterion Affine projection Algorithm and Its Performance Analysis

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2022年 70卷 3540-3550页

作者： Qiu, Chen Qian, Guobing Wang, Shiyuan Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China

Recently, affine projection algorithm has been extensively studied in the Gaussian noise environment. However, the performance of affine projection algorithm will deteriorate rapidly in the presence of impulsive noise and other non-Gaussian noise. To address this issue, this paper proposes a novel affine projection algorithm based on the complex Gaussian kernel function, called widely linear maximum complex correntropy criterion affine projection algorithm (WL-MCCC-APA). With the maximum complex correntropy criterion (MCCC), the robustness of affine projection algorithm is improved significantly in the non-Gaussian noise environment, especially in the presence of impulsive noise. Meanwhile, a variable step size WL-MCCC-APA (VSS-WL-MCCC-APA) method based on fixed-point theory is proposed to further balance the convergence rate and steady-state misalignment of the algorithm. Finally, the step size boundary analysis and steady-state analysis are presented for theoretical analysis. Simulation results verify the correctness of obtained theoretical results and the superiority of the proposed WL-MCCC-APA and VSS-WL -MCCC-APA.

关键词： Signal processing algorithms projection algorithms Optimized production technology Kernel Filtering algorithms Cost function Convergence Widely linear affine projection maximum complex correntropy criterion variable step size

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A Simple Check Polytope projection Penalized Algorithm for ADMM Decoding of LDPC Codes

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IEEE ACCESS 2023年 11卷 2524-2530页

作者： Liu, Huiyang He, Pingquan Jiang, Yun Zhang, Qinglin Xia, Qiaoqiao Cent China Normal Univ Coll Phys Sci & Technol Wuhan 430079 Peoples R China

ADMM penalized decoding method for Low-Density Parity-Check (LDPC) Codes can improve the frame error rate (FER) performance than the standard ADMM decoder by adding penalty terms to the objective function. However, penalty parameter optimization of the penalty terms is very difficult and extremely time-consuming. Additionally, the Euclidean projection onto the check polytope is the most complex part of ADMM-based decoding algorithms. In this paper, by dynamically choosing even-vertex in the check polytope closest to the input vector as the approximate projection, a simple and novel check polytope projection penalized algorithm for ADMM decoding is proposed which can avoid the tedious work of penalty parameter optimization and simplify the check polytope projection. The simulation results show that the proposed algorithm can substantially reduce the projection time while achieving better FER performance when compared with the existing penalized decoding. In particular, the proposed algorithm can save the decoding time by 23% to 41% compared with ADMM-PD-LSA algorithm.

关键词： Maximum likelihood decoding Approximation algorithms Convex functions projection algorithms Optimization Heuristic algorithms Mathematical models Alternating direction method of multipliers (ADMM) low-density parity-check (LDPC) codes penalty terms check polytope projection

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Cooperative Set Aggregation of Second-Order Multiagent Systems: Approximate projection and Prescribed Performance

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IEEE TRANSACTIONS ON CYBERNETICS 2020年第3期50卷 957-970页

作者： Yue, Dandan Meng, Ziyang Tsinghua Univ Dept Precis Instrument Beijing 100084 Peoples R China

This paper studies the cooperative set aggregation problem for second-order multiagent systems by utilizing the approximate projection algorithm. First, an aggregation law that uses the approximate projection is proposed, where the feasible set of the approximate projection points is established based on an Euclidean distance with respect to the targeted set and a deviated angle with respect to the exact projection point. Under the proposed law, the position vectors of all the agents are shown to reach an agreement in the intersection of their individual targeted sets and the velocity vector of each agent is shown to converge to zero. Then, a time-dependent performance bound is set for the norm of the weighted error of the relative positions among neighboring agents and the absolute velocity of the agent, and a performance-guaranteed aggregation controller is designed to guarantee the prescribed transient performance. During the process of aggregation, the norm of the weighted error is shown to not exceed the performance bound. The convergence conditions of the proposed algorithms with respect to the control strength and the terms induced by the approximate projection are obtained by using the techniques of convex analysis and Lyapunov stability. Simulations are provided to validate the theoretical results.

关键词： Convergence projection algorithms Transient analysis Multi-agent systems Decentralized control Optimization Approximation algorithms Approximate projection directed graph guaranteed performance second-order multiagent systems (MASs) set aggregation

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A Block Recognition System Constructed by Using a Novel projection Algorithmand Convolution Neural Networks

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IEEE ACCESS 2017年 5卷 23891-23900页

作者： Chou, Chien-Hsing Su, Yu-Sheng Tamkang Univ Dept Elect Engn New Taipei 251 Taiwan Natl Cent Univ Res Ctr Adv Sci & Technol Taoyuan 320 Taiwan

In the age of Industry 4.0, the techniques of artificial intelligence and pattern recognition play a critical role to develop the smart factories. In this paper, a block recognition system, named e-Block, was developed by using a novel projection algorithm and the convolution neural networks. The developed system displays a picture of the target object (e.g., a car or a house), and the children follow the instructions provided by the system and use the various blocks to build the object. Subsequently, this system compares the assembled block with the target object and determines whether the shape is identical. To identify the assembled block, this system applies Kinect to obtain information on the depth of the object and a new projection algorithm is proposed for converting the depth information into three feature images. By integrating three feature images, the convolution neural networks (CNN) are employed to construct the classifier to identify the assembled block. In the experiments conducted in this paper, the CNN classifier was compared with three classification algorithms. The experimental results show that the CNN classifier can accurately recognizes whether the assembled object is identical to the target object and outperform the compared classification algorithms. In additions, the experimental results also reveal that the proposed recognition algorithm can be a useful technique for applying in various applications of Industry 4.0.

关键词： Building block projection algorithms pattern recognition convolution neural networks kinect

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CONVERGENCE OF GRADIENT projection ROUTING METHODS IN AN ASYNCHRONOUS STOCHASTIC QUASI-STATIC VIRTUAL CIRCUIT NETWORK

引用

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 1989年第1期34卷 20-33页

作者： TSAI, WK Department of Electrical Engineering Texas A and M University College Station TX USA

The convergence of the gradient projection algorithms for optimal routing in virtual circuit data networks proposed by D.P. Bertsekas (1982) is studied. The routing model explicitly takes into account stochastic generation and termination of virtual circuits, distributed asynchronous routing updates, inaccurate flow measurement, and delays in forwarding control packets. The problem of assigning paths for incoming sessions (or virtual circuits) to implement the gradient projection algorithms is also studied. A metering rule based on deficiency in a desired number of virtual circuits is proposed and analyzed. It is shown that the proposed metering rule is better than a randomized rule in some sense. The gradient projection routing algorithms implemented either by the metering rule or the randomized rule are shown to converge to a neighborhood of a long-term optimal routing.< >

关键词： Convergence Routing Stochastic processes Circuits projection algorithms Delay Fluid flow measurement Traffic control Newton method Intelligent networks

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Consensus of Multi-Agent Systems Under Binary-Valued Measurements and Recursive projection Algorithm

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2020年第6期65卷 2678-2685页

作者： Wang, Ting Zhang, Hang Zhao, Yanlong Chinese Acad Sci Acad Math & Syst Sci Inst Syst Sci Key Lab Syst & Control Beijing 100190 Peoples R China

This paper studies consensus problems of multi-agent systems with binary-valued communications. Different from most existing works, the agents considered in this paper can only get binary-valued observations of its neighbors' states with random noises. A consensus algorithm is proposed: first, each agent estimates its neighbors' states by the recursive projection algorithm;then, each agent designs the control timely based on the estimates. It is proved that the estimates of the states can converge to the true states with a faster convergence rate than that in the parameter estimation. Moreover, the states of the agents can achieve mean-square consensus, and the corresponding consensus speed can achieve O(1/t) under certain conditions. Finally, simulations are given to demonstrate the theoretical results.

关键词： Convergence Consensus algorithm projection algorithms Noise measurement Estimation Multi-agent systems Approximation algorithms Binary-valued communications convergence convergence rate consensus control estimate multi-agent systems recursive projection algorithm

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