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A convergent smoothing algorithm for training max-min fuzzy neural networks

NEUROCOMPUTING 2017年 260卷 404-410页

作者： Li, Long Qiao, Zhijun Liu, Yan Chen, Yuan Hengyang Normal Univ Coll Math & Stat Hengyang 421008 Peoples R China Univ Texas Rio Grande Valley Sch Math & Stat Sci Edinburg TX 78539 USA Dalian Polytech Univ Dept Appl Math Dalian 116034 Peoples R China

In this paper, a smooth function is constructed to approximate the nonsmooth output of max-min fuzzy neural networks (FNNs) and its approximation is also presented. In place of the output of max-min FNNs by its smoothing approximation function, the error function, defining the discrepancy between the actual outputs and desired outputs of max-min FNNs, becomes a continuously differentiable function. Then, a smoothing gradient decent-based algorithm with Armijo-Goldstein step size rule is formulated to train max-min FNNs. Based on the existing convergent result, the convergence of our proposed algorithm can easily be obtained. Furthermore, the proposed algorithm also provides a feasible procedure to solve fuzzy relational equations with max-min composition. Finally, some numerical examples are implemented to support our results and demonstrate that the proposed smoothing algorithm has better learning performance than other two gradient decent-based algorithms. (C) 2017 Elsevier B.V. All rights reserved.

关键词： smoothing algorithm Max-min fuzzy neural network Convergence Fuzzy relational equation

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Application of Square-Root Unscented Kalman Filter smoothing algorithm in Tracking Underwater Target

Application of Square-Root Unscented Kalman Filter Smoothing...

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2017 4th International Conference on Machinery,Materials and Computer(MACMC 2017)

作者： Qiguo YAO Yuxiang SU Lili LI School of Naval Architecture ＆ Mechanical-electrical Engineering Zhejiang Ocean University

In passive tracking, the nonlinearity may cause computational complication and precision degradation. To solve this problem, a novel filtering-smoothing algorithm based on Square-Root Unscented Kalman Filter（SR-UKFS） is proposed to track underwater target. In the SR-UKFS algorithm, the Square-Root Unscented Kalman Filter（SR-UKF） is used as forward-filtering algorithm to provide current location results, and the Rauch-Tung-Striebel（RTS） algorithm smoothes the previous state vector and covariance matrix using the current location results. Comparative analysis and validation are made on the tracking performances of SR-UKFS algorithm and SR-UKF algorithm, and the simulation results show that, under the same conditions, the SR-UKFS can more effectively improve the tracking precision than the SR-UKF algorithm. The SR-UKFS algorithm can reduce nearly 59% of the position error and nearly 54% of the velocity error.

关键词： Target Tracking Square-root Unscented Kalman Filter smoothing algorithm Forward-filtering Backward-smoothing

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Variable structure multiple model fixed-interval smoothing

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Chinese Journal of Aeronautics 2023年第2期36卷 139-148页

作者： Bolun ZHANG Yongxin GAO Zhansheng DUAN Faculty of Electronic and Information Engineering School of Automation Science and EngineeringXi’an Jiaotong UniversityXi'an 710049China

This paper focuses on fixed-interval smoothing for stochastic hybrid *** the truth-mode mismatch is encountered,existing smoothing methods based on fixed structure of model-set have significant performance degradation and are *** develop a fixedinterval smoothing method based on forward-and backward-filtering in the Variable Structure Multiple Model(VSMM)framework in this *** propose to use the Simplified Equivalent model Interacting Multiple Model(SEIMM)in the forward and the backward filters to handle the difficulty of different mode-sets used in both filters,and design a re-filtering procedure in the model-switching stage to enhance the estimation *** improve the computational efficiency,we make the basic model-set adaptive by the Likely-Model Set(LMS)*** turns out that the smoothing performance is further improved by the LMS due to less competition among *** results are provided to demonstrate the better performance and the computational efficiency of our proposed smoothing algorithms.

关键词： Fixed-interval smoothing Model-set adaptation Multiple model estimation smoothing algorithm Variable structure

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smoothing techniques in solving non-Lipschitz absolute value equations

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2023年第4期100卷 867-879页

作者： Yilmaz, Nurullah Sahiner, Ahmet Suleyman Demirel Univ Dept Math Isparta Turkiye

In this study, we define for the first time the non-Lipschitz generalization of absolute value equations and concentrate on solving the problem of non-Lipschitz absolute value equations based on smoothing techniques. Two different types of smoothing techniques which are local and global ones are considered in smoothing process of the problem. With the help of these smoothing techniques, the non-Lipschitz absolute value equations are reformulated as a family of parametrized smooth equations. Two new algorithms are developed to solve the problem by the help of smoothing functions. Finally, the numerical experiments have been performed to illustrate the efficiency of the new algorithms.

关键词： smoothing techniques smoothing algorithm absolute value equations non-Lipschitz functions Newton algorithm

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Sensor Saturation Compensated smoothing algorithm for Inertial Sensor Based Motion Tracking

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SENSORS 2014年第5期14卷 8167-8188页

作者： Quoc Khanh Dang Suh, Young Soo Univ Ulsan Dept Elect Engn Ulsan 680749 South Korea

In this paper, a smoothing algorithm for compensating inertial sensor saturation is proposed. The sensor saturation happens when a sensor measures a value that is larger than its dynamic range. This can lead to a considerable accumulated error. To compensate the lost information in saturated sensor data, we propose a smoothing algorithm in which the saturation compensation is formulated as an optimization problem. Based on a standard smoothing algorithm with zero velocity intervals, two saturation estimation methods were proposed. Simulation and experiments prove that the proposed methods are effective in compensating the sensor saturation.

关键词： sensor saturation compensation smoothing algorithm

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A Coprime and Periodic Pilot Design for ISAC System 25

A Coprime and Periodic Pilot Design for ISAC System

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IEEE Wireless Communications and Networking Conference (IEEE WCNC)

作者： Mei, Dongyang Wei, Zhiqing Chen, Xu Wang, Lin Feng, Zhiyong Beijing Univ Posts & Telecommun Key Lab Universal Wireless Commun Minist Educ Beijing 100876 Peoples R China

ISBN: (纸本)9798350303582;9798350303599

In the Integrated Sensing and Communication (ISAC) system, the pilot signal has high sensing performance due to its good autocorrelation and high transmit power. However, the equally spaced pilot signal reduces the maximum unambiguous range and velocity compared with the OFDM signal with continuous resources, limiting the sensing performance of base station (BS). Additionally, BS fails to estimate the distances and velocities of multiple targets in coherent signals. To address these problems, we propose a pilot design scheme with coprime and periodic stepping values for pilot indices. Theoretical analysis and simulation results demonstrate that the proposed pilot signal does not reduce the maximum unambiguous range and velocity, which can be processed by the smoothing algorithm and the multiple signal classification (MUSIC) algorithm to accurately estimate the distances and velocities of multiple targets in coherent signals.

关键词： Integrated sensing and communication Pilot design Maximum unambiguous range and velocity smoothing algorithm Multiple signal classification algorithm

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Tool-path continuity determination based on machine learning method

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2022年第1-2期119卷 403-420页

作者： Zhou, Bo Tian, Tongtong Zhao, Jibin Liu, Dianhai Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Peoples R China Chinese Acad Sci Inst Robot & Intelligent Mfg Shenyang 110169 Peoples R China

Computer-aided manufacturing (CAM) software outputs machining data by encoding a tool-path into a series of G-codes which are composed of various lengths of line segments. The discontinuities of these line segments may cause inefficiency for computer numerical control (CNC) system. To achieve high-speed continuous motions, corner smoothing algorithms based on look-ahead methods are widely used. However, it is difficult to meet smoothing trajectories in real-time requirements. Based on machine learning method, in this paper, a support vector machine (SVM) system is presented for directly outputting classification results of the various geometric continuities at the transition corners. The feature values used for generating continuity classification model are extracted from sampling paths of the previous publication work: the machining parameters, length, fairness criteria, the root mean square (RMS) contour errors, and dominant stage type of movement of each sampling path are calculated. The acceleration/deceleration (ACC/DEC) feedrate planning scheme is used to determine the feedrate at the transition corners. Simulations and experiments show that the proposed algorithm can realize accurately and efficiently continuity classification in real-time requirements under the conditions of machining accuracy.

关键词： smoothing algorithm Machine learning Support vector machine Continuity Parametric curve

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A continuous RRT*-based path planning method for non-holonomic mobile robots using B-spline curves

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2022年第7期14卷 8693-8702页

作者： Eshtehardian, S. A. Khodaygan, S. Sharif Univ Technol Dept Mech Engn Tehran Iran

Rapidly exploring random trees (RRT) are sampling-based approaches being widely applied for path planning of mobile robots. Since the output of these algorithms usually is a stream of discrete lines involving discontinuity at the linking points, kinematic constraints restrict the robot's movements. Consequently, robots may not pass discrete points in the path correctly. Hence, the using CAGD (Computer-Aided Geometry Design) curves can run simultaneously alongside those algorithms or may run after that to make a smooth path and that's the way in which non-holonomic constraints can be considered perfect and robots can be droved autonomously across them about the collision detection method which executed by the main sampling-based algorithm like RRT*. In this paper, an approach based on the combination of RRT* and B-spline is proposed for smoothing the path which is generated by RRT*-based algorithms, which are one of the most famous groups of algorithms in artificial intelligence. Some new functions are added to the outcome of the RRT* algorithm. To avoid collision in the generated path, some corrections are also provided. Finally, for illustrating the efficiency of the proposed method, the algorithm is implemented in the simulation environment of Webots(R) and for verification, the obtained results are compared and discussed.

关键词： Path planning RRT algorithm smoothing algorithm Non-holonomic mobile robots B-spline curves

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A Collision-Free G² Continuous Path-smoothing algorithm Using Quadratic Polynomial Interpolation

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INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 2014年第12期11卷 194-194页

作者： Chang, Seong-Ryong Huh, Uk-Youl Inha Univ Dept Elect Engn Inchon South Korea

Most path-planning algorithms are used to obtain a collision-free path without considering continuity. On the other hand, a continuous path is needed for stable movement. In this paper, the searched path was converted into a G(2) continuous path using the modified quadratic polynomial and membership function interpolation algorithm. It is simple, unique and provides a good geometric interpretation. In addition, a collision-checking and improvement algorithm is proposed. The collision-checking algorithm can check the collisions of a smoothed path. If collisions are detected, the collision improvement algorithm modifies the collision path to a collision-free path. The collision improvement algorithm uses a geometric method. This method uses the perpendicular line between a collision position and the collision piecewise linear path. The sub-waypoint is added, and the QPMI algorithm is applied again. As a result, the collision-smoothed path is converted into a collision-free smooth path without changing the continuity.

关键词： Continuous path Function approximation Interpolation Path planning Path smoothing Robot motion smoothing algorithm Smooth path Vehicle navigation

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A G² Continuous Path-smoothing algorithm Using Modified Quadratic Polynomial Interpolation

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INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 2014年第2期11卷 25-25页

作者： Huh, Uk-Youl Chang, Seong-Ryong Inha Univ Inchon South Korea

Path searching algorithm is one of the main topics in studies on path planning. These algorithms are used to avoiding obstacles and find paths from starting point to target point. There are dynamic problems that must be addressed when these paths are applied in real environments. In order to be applicable in actual situations, the path must be a smooth path. A smooth path is a path that maintains continuity. Continuity is decided by the differential values of the path. In order to be G(2) continuous, the secondary differential values of the path must be connected throughout the path. In this paper, the interpolation method is used to construct continuous paths. The quadratic polynomial interpolation is a simple method for obtaining continuous paths about three points. The proposed algorithm makes a connection of three points with curves and the proposed path is rotated using the parametric method in order to make the path optimal and smooth. The polynomials expand to the next three points and they merge into the entire path using the membership functions with G(2) continuity.

关键词： Continuous Path Curve Fitting Function Approximation Interpolation Path Planning Robot Motion smoothing algorithm Smooth Path Vehicle Navigation

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