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A robust and Consistent algorithm for Intersecting Convex Polyhedra

Computer Graphics Forum 1994年第3期13卷 45-54页

作者： Sugihara, Kokichi Department of Mathematical Engineering Faculty of Engineering University of Tokyo Tokyo 113 7‐3‐1 Hongo Bunkyo‐ku Japan

This paper presents a numerically robust and topologically consistent algorithm for intersecting convex polyhedra. This algorithm is new in the sense that the consistency issue is completely separated from the numerical error issue. The intersection operation is combinatorially abstracted as the operation of changing the vertex‐edge graphs associated with the input polyhedra, and numerical computation is employed only for choosing the branch of processing which is most likely to lead to the correct solution of the problem. Hence, the resultant algorithm is completely free from topological inconsistency. © 1994 Eurographics Association

关键词： combinatorial abstraction convex polyhedron robust algorithm solid modeling

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Adaptive Fault Estimation for Dynamics of High Speed Train Based on robust UKF algorithm

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Journal of Harbin Institute of Technology(New Series) 2023年第1期30卷 61-72页

作者： Kexin Li Tiantian Liang School of Automation and Electrical Engineering Dalian Jiaotong UniversityDalian 116028China

This paper proposes an adaptive unscented Kalman filter algorithm(ARUKF)to implement fault estimation for the dynamics of high⁃speed train(HST)with measurement uncertainty and time⁃varying noise with unknown ***,regarding the actuator and sensor fault as the auxiliary variables of the dynamics of HST,an augmented system is established,and the fault estimation problem for dynamics of HST is formulated as the state estimation of the augmented ***,considering the measurement uncertainties,a robust lower bound is proposed to modify the update of the UKF to decrease the influence of measurement uncertainty on the filtering ***,considering the unknown time⁃varying noise of the dynamics of HST,an adaptive UKF algorithm based on moving window is proposed to estimate the time⁃varying noise so that accurate concurrent actuator and sensor fault estimations of dynamics of HST is ***,a five-car model of HST is given to show the effectiveness of this method.

关键词： high speed train Kalman filter adaptive algorithm robust algorithm unknown noise measurement uncertainty

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A robust Adaptive algorithm using Inverse Square Root Cost Function for Underwater Channel Estimation 15

A Robust Adaptive Algorithm using Inverse Square Root Cost F...

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15th IEEE International Conference on Advanced Networks and Telecommunications Systems (IEEE ANTS)

作者： Mishra, Bishnu Prasad Wilson, Annet Mary Panigrahi, Trilochan Sabat, Samrat L. Natl Inst Technol Goa Dept Elect & Commun Engn Ponda Goa India Univ Hyderabad Sch Phys Ctr Adv Studies Elect Sci & Technol Hyderabad 500046 India

ISBN: (纸本)9781665448932

Channel estimation in underwater acoustic (UWA) communication is challenging due to the presence of impulsive noise, extreme multipath spread, and the time-varying nature of the environment. In an impulsive environment, gradient-based algorithms based on the error square cost function fails. Maximum correntropy criteria (MCC), logarithmic cost (LCLMA), and sigmoidal cost functions are used to minimize the effect of impulsive noise with an added cost of convergence rate and complexity. This paper presents a robust cost function, namely Inverse Square Root (ISR), to mitigate the above issue. The slope of the ISR cost function is negligible for high impulsive noise. We compare the effectiveness of the ISR cost function with state-of-the-art cost functions by varying the impulsive noise probability in the UWA channel. In comparison to MCC and LCLMA algorithms, the simulation results show that ISR cost function-based learning converges faster in the presence of a higher percentage of impulsive noise with less computing complexity.

关键词： Acoustic channel estimation robust algorithm Impulsive noise Inverse square root mean square deviation

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A robust NLMS algorithm WITH A NOVEL NOISE MODELING BASED ON STATIONARY/NONSTATIONARY NOISE DECOMPOSITION

A ROBUST NLMS ALGORITHM WITH A NOVEL NOISE MODELING BASED ON...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Sugiyama, Akihiko NEC Common Platform Software Res Labs Kawasaki Kanagawa 2118666 Japan

ISBN: (纸本)9781424423538

This paper proposes a robust NLMS algorithm with a novel noise modeling based on stationary/nonstationary noise decomposition. The ambient noise including the near-end signal is modeled as a weighted sum of the stationary and the nonstationary, components. These components are independently estimated with an appropriate time constant for better accuracy. The estimates are weighted by the stationary/nonstationary likelihood before summation. The integrated noise estimate controls the coefficient adaptation stepsize such that it is an upward convex function of the reference input with a noise offset for robustness. Evaluations in a fullband and a subband echo cancellation scenarios show that ERLE has been improved by as much as 40 dB over the algorithm with a conventional noise model in both single- and double-talk sections with no double-talk detection.

关键词： Adaptive filter robust algorithm Noise model Echo cancellation Double-talk

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robust and fast algorithm for extracting the periodic feature from jet engine modulation signals

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JOURNAL OF ENGINEERING-JOE 2019年第20期2019卷 6507-6511页

作者： Sun, Jingming Yu, Junpeng Nanjing Res Inst Elect Technol Nanjing 210039 Jiangsu Peoples R China CETC Key Lab IntelliSense Technol Nanjing 210039 Jiangsu Peoples R China

Jet engine modulation (JEM), a modulation phenomenon induced by the rotating structure of jet engines, is a representative feature extracted from the radar returns for aircraft target recognition. As one of the most significant periodic characteristics of JEM, the chopping frequency plays an important role in aircraft target recognition. However, existing methods either need complicated logical algorithms to get an accurate estimation of the chopping frequency or exploit the chopping frequency as priori information for further feature extraction, and neither of these two scenarios is practical. Here, the authors propose a robust and fast algorithm for extracting the chopping frequency, which uses wavelet decomposition combined with autocorrelation to process the analytic form of the JEM signal. Application results of measured JEM signals demonstrate that the proposed algorithm is effective and practical for stable and accurate extraction of the periodic feature from JEM signals.

关键词： jet engines image processing low-pass filters radar target recognition Wigner distribution feature extraction wavelet transforms significant periodic characteristics chopping frequency logical algorithms feature extraction robust algorithm JEM signal measured JEM signals stable extraction accurate extraction aircraft target recognition radar returns representative feature jet engines rotating structure modulation phenomenon jet engine modulation signals periodic feature fast algorithm

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robust management in smart grids in the presence of prosumers based on PV-storage

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ENERGY REPORTS 2025年 13卷 2482-2501页

作者： Salehabadi, Kazem Moghaddam, Mahmoud Samiei Davarzani, Reza Hoseinpour, Hesamodin Islamic Azad Univ Dept Elect Engn Shahrood Branch Shahrood Iran Islamic Azad Univ Dept Elect Engn Damghan Branch Damghan Iran

This research introduces a novel application of Mixed Integer Second Order Conic Programming (MISOCP) combined with a tailored Column-and-Constraint Generation (C&CG) algorithm for the advanced management of energy and load in dynamic smart grids with prosumers. The framework addresses critical gaps in existing methods by integrating a customized multi-objective optimization approach to minimize energy losses, voltage deviations, load shedding costs, and prosumer electricity expenses. A novel aspect of the methodology is its ability to handle uncertainties in renewable generation and load demand, ensuring robust and scalable optimization across diverse grid scenarios. The proposed approach is validated through extensive simulations on the IEEE 33-node system, the IEEE 118-bus system, and a real-world Tehran distribution grid, showcasing its practicality and effectiveness. Results demonstrate significant improvements, including a 15.3 % reduction in grid losses, a 12.4 % improvement in voltage stability, and enhanced prosumer participation in energy transactions. Furthermore, the model achieves superior performance in scalability, computational efficiency, and adaptability compared to existing methods. This study contributes a comprehensive and innovative framework that enhances the sustainability and efficiency of active distribution grids, making it a valuable tool for modern smart grid applications.

关键词： Smart grid Energy storage system Renewable resources Prosumers robust algorithm

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robust algorithms for face-based representations

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COMPUTER-AIDED DESIGN 1997年第2期29卷 135-146页

作者： Higashi, M Torihara, F Takeuchi, N Sata, T Saitoh, T Hosaka, M TOKYO DENKI UNIV CHIYODA KUTOKYO 101JAPAN

This paper proposes a new face-based data structure and robust algorithms for processing polyhedra. The face-based structure is introduced for representing designers' intentions and constraints on faces without redundancy as well as machining features for the faces, and for handling computational errors. To construct the algorithms, the following three principles are employed. Fundamental data are coefficients of plane equations, and coordinate values of vertices which include computational errors are treated as secondary. Incidence tests among geometrical elements such as vertices, edges and faces are performed based on a determinant value of four faces. A local topological structure, where many faces intersect near a point and ambiguities of the topology remain, is determined as a tree structure so as not to make small faces according to the global feature of the shape in terms of a sequence of the face segments and edge classification as concave and convex. In this paper, the incidence test is explained geometrically. algorithms for Boolean set operations are presented along with classification of incidence patterns, and some examples executed with them are shown. Copyright (C) 1996 Elsevier Science Ltd

关键词： solid modelling face-based representation robust algorithm

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robust algorithmS WITH POLYNOMIAL LOSS FOR NEAR-UNANIMITY CSPs

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SIAM JOURNAL ON COMPUTING 2019年第6期48卷 1763-1795页

作者： Dalmau, Victor Kozik, Marcin Krokhin, Andrei Makarychev, Konstantin Makarychev, Yury Oprsal, Jakub Univ Pompeu Fabra Dept Informat & Commun Technol Barcelona 08018 Spain Jagiellonian Univ Fac Math & Comp Sci Dept Theoret Comp Sci PL-30348 Krakow Poland Univ Durham Dept Comp Sci Durham DH1 3LE England Northwestern Univ Dept Elect Engn & Comp Sci Evanston IL 60208 USA Toyota Technol Inst Chicago IL 60637 USA

An instance of the constraint satisfaction problem (CSP) is given by a family of constraints on overlapping sets of variables, and the goal is to assign values from a fixed domain to the variables so that all constraints are satisfied. In the optimization version, the goal is to maximize the number of satisfied constraints. An approximation algorithm for a CSP is called robust if it outputs an assignment satisfying an (1 - g(epsilon))-fraction of constraints on any (1 - epsilon)-satisfiable instance, where the loss function g is such that g(epsilon) -> 0 as epsilon -> 0. We study how the robust approximability of CSPs depends on the set of constraint relations allowed in instances, the so-called constraint language. All constraint languages admitting a robust polynomial-time algorithm (with some g) have been characterized by Barto and Kozik, with the general bound on the loss g being doubly exponential, specifically g(epsilon) = O((log log(1/epsilon))/ log(1/epsilon)). It is natural to ask when a better loss can be achieved, in particular polynomial loss g(epsilon) = O(epsilon(1/k)) for some constant k. In this paper, we consider CSPs with a constraint language having a near-unanimity polymorphism. This general condition almost matches a known necessary condition for having a robust algorithm with polynomial loss. We give two randomized robust algorithms with polynomial loss for such CSPs: one works for any near-unanimity polymorphism and the parameter k in the loss depends on the size of the domain and the arity of the relations in Gamma, while the other works for a special ternary near-unanimity operation called the dual discriminator with k = 2 for any domain size. In the latter case, the CSP is a common generalization of UNIQUE GAMES with a fixed domain and 2-SAT. In the former case, we use the algebraic approach to the CSP. Both cases use the standard semidefinite programming relaxation for the CSP.

关键词： constraint satisfaction approximation algorithms robust algorithm near-unanimity polymorphism

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robust algorithms for principal component analysis

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PATTERN RECOGNITION LETTERS 1999年第9期20卷 927-933页

作者： Yang, TN Wang, SD Natl Taiwan Univ Dept Elect Engn Taipei 106 Taiwan

In this paper, we address the issues related to the design of fuzzy robust principal component analysis (FRPCA) algorithms. The design of robust principal component analysis has been studied in the literature of statistics for over two decades. More recently Xu and Yuille proposed a family of online robust principal component analysis based on statistical physics approach. We extend Xu and Yuille's objective function by using fuzzy membership and derive improved algorithms that can extract the appropriate principal components from the spoiled data set. The difficulty of selecting an appropriate hard threshold in Xu and Yuille's approach is alleviated by replacing the threshold by an automatically selected soft threshold in FRPCA. Artificially generated data sets are used to evaluate the performance of various PCA algorithms. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： principal component analysis robust algorithm noise clustering neural networks fuzzy theory

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A robust filtered-s LMS algorithm for nonlinear active noise control

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APPLIED ACOUSTICS 2012年第8期73卷 836-841页

作者： George, Nithin V. Panda, Ganapati Indian Inst Technol Sch Elect Sci Bhubaneswar 751013 Odisha India

The performance of a nonlinear active noise control (ANC) system based on the recently developed filtered-s least mean square (FsLMS) algorithm deteriorates when strong disturbances in the ANC system are acquired by the microphones. To surmount this shortcoming, a novel robust FsLMS (RFsLMS) algorithm is proposed for a functional link artificial neural network (FLANN) based ANC system. The new ANC system is least sensitive to such disturbances and does not call for any prior information on the noise characteristics. The results obtained from simulation study establish the effectiveness of this new ANC scheme. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Active noise control robust algorithm Filtered-s least mean square algorithm Functional link artificial neural network Impulsive noise

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