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Journal articles on the topic 'Perturbation-Based methods'

Author: Grafiati

Published: 7 July 2024

Last updated: 31 July 2025

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1

Hongxing, Li. "Fuzzy clustering methods based on perturbation." Fuzzy Sets and Systems 33, no. 3 (1989): 291–302. http://dx.doi.org/10.1016/0165-0114(89)90119-x.

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Martinelli, M., A. Dervieux, L. Hascoet, V. Pascual, and A. Belme. "AD-based perturbation methods for uncertainties and errors." International Journal of Engineering Systems Modelling and Simulation 2, no. 1/2 (2010): 65. http://dx.doi.org/10.1504/ijesms.2010.031872.

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San-Juan, Juan Félix, Montserrat San-Martín, Iván Pérez, and Rosario López. "Hybrid perturbation methods based on statistical time series models." Advances in Space Research 57, no. 8 (2016): 1641–51. http://dx.doi.org/10.1016/j.asr.2015.05.025.

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Chioua, Moncef, Bala Srinivasan, Michel Perrier, and Martin Guay. "EFFECT OF EXCITATION FREQUENCY IN PERTURBATION-BASED EXTREMUM SEEKING METHODS." IFAC Proceedings Volumes 40, no. 5 (2007): 123–28. http://dx.doi.org/10.3182/20070606-3-mx-2915.00019.

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5

Ivanovs, Maksims, Roberts Kadikis, and Kaspars Ozols. "Perturbation-based methods for explaining deep neural networks: A survey." Pattern Recognition Letters 150 (October 2021): 228–34. http://dx.doi.org/10.1016/j.patrec.2021.06.030.

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Liu, Song-Tao, and Yuesheng Xu. "Galerkin Methods Based on Hermite Splines for Singular Perturbation Problems." SIAM Journal on Numerical Analysis 43, no. 6 (2006): 2607–23. http://dx.doi.org/10.1137/040607411.

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7

El Mokhtari, Rachid, Jean-Marc Cadou, and Michel Potier-Ferry. "A two grid algorithm based on perturbation and homotopy methods." Comptes Rendus Mécanique 330, no. 12 (2002): 825–30. http://dx.doi.org/10.1016/s1631-0721(02)01548-6.

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8

Zhang, Yale, and J. Fraser Forbes. "Performance Analysis of Perturbation-Based Methods for Real-Time Optimization." Canadian Journal of Chemical Engineering 84, no. 2 (2008): 209–18. http://dx.doi.org/10.1002/cjce.5450840208.

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Li, Lan, Yong Hui He, and Bo Wang. "Comparison of Methods of Maximum Power Point Tracking of Photovoltaic Cells." Applied Mechanics and Materials 380-384 (August 2013): 3362–65. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3362.

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According to engineering mathematics model of solar photovoltaic cells, a simulation model of photovoltaic cells was established in Matlab. In view of problem that it is difficult to get higher tracking accuracy and response speed by use of perturbation and observation method which applied fixed perturbation step, the paper proposed an improved perturbation and observation method based on variable step. Through simulating photovoltaic cells control system, simulation curves of two kinds of methods of maximum power point tracking were compared. The simulation results show that the photovoltaic

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Cha, Philip D., and Austin Shin. "Perturbation Methods for the Eigencharacteristics of Symmetric and Asymmetric Systems." Shock and Vibration 2018 (October 17, 2018): 1–25. http://dx.doi.org/10.1155/2018/8609138.

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Dynamic analysis for a vibratory system typically begins with an evaluation of its eigencharacteristics. However, when design changes are introduced, the eigensolutions of the system change and thus must be recomputed. In this paper, three different methods based on the eigenvalue perturbation theory are introduced to analyze the effects of modifications without performing a potentially time-consuming and costly reanalysis. They will be referred to as the straightforward perturbation method, the incremental perturbation method, and the triple product method. In the straightforward perturbation

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Yang, Xiao-Dong, Ming Liu, Wei Zhang, Ying-Jing Qian, and Roderick V. N. Melnik. "On the Perturbation Methods for Vibration Analysis of Linear Time-Varying Systems." International Journal of Applied Mechanics 08, no. 03 (2016): 1650035. http://dx.doi.org/10.1142/s1758825116500356.

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Some perturbation methods in the studying vibrations of the linear time-varying (LTV) system are discussed. Three classical perturbation methods, namely, averaging method, harmonic balance method, and multiple scales method with linear scales, have been used from a new perspective based on analytical approximations to the corresponding LTV ordinary differential equations. The deploying beam model has been taken as an example to validate the explicit approximate solutions obtained by these perturbation methods. It is demonstrated that such approximate solutions have good agreement with numerica

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Chen, Bilian, Yajun Xie, and Changfeng Ma. "SOME HIGH ORDER ITERATIVE METHODS FOR NONLINEAR EQUATIONS BASED ON THE MODIFIED HOMOTOPY PERTURBATION METHODS." Asian-European Journal of Mathematics 03, no. 03 (2010): 395–408. http://dx.doi.org/10.1142/s1793557110000349.

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In this paper, we present some efficient iterative methods for solving nonlinear equation (systems of nonlinear equations, respectively) by using modified homotopy perturbation methods. We also discuss the convergence criteria of the present methods. Some numerical examples are given to illustrate the performance and efficiency of the proposed methods.

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Lazovskaya, Tatiana, Galina Malykhina, and Dmitry Tarkhov. "Physics-Based Neural Network Methods for Solving Parameterized Singular Perturbation Problem." Computation 9, no. 9 (2021): 97. http://dx.doi.org/10.3390/computation9090097.

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This work is devoted to the description and comparative study of some methods of mathematical modeling. We consider methods that can be applied for building cyber-physical systems and digital twins. These application areas add to the usual accuracy requirements for a model the need to be adaptable to new data and the small computational complexity allows it to be used in embedded systems. First, we regard the finite element method as one of the “pure” physics-based modeling methods and the general neural network approach as a variant of machine learning modeling with physics-based regularizati

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Langlands, T. A. M., and D. L. S. McElwain. "A modified Hertzian foil rolling model: approximations based on perturbation methods." International Journal of Mechanical Sciences 44, no. 8 (2002): 1715–30. http://dx.doi.org/10.1016/s0020-7403(02)00058-9.

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Paralič, Ján, Michal Kolárik, Zuzana Paraličová, Oliver Lohaj, and Adam Jozefík. "Perturbation-Based Explainable AI for ECG Sensor Data." Applied Sciences 13, no. 3 (2023): 1805. http://dx.doi.org/10.3390/app13031805.

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Deep neural network models have produced significant results in solving various challenging tasks, including medical diagnostics. To increase the credibility of these black-box models in the eyes of doctors, it is necessary to focus on their explainability. Several papers have been published combining deep learning methods with selected types of explainability methods, usually aimed at analyzing medical image data, including ECG images. The ECG is specific because its image representation is only a secondary visualization of stream data from sensors. However, explainability methods for stream

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Li, Mengyang, Fengguang Su, Ou Wu, and Ji Zhang. "Logit Perturbation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 2 (2022): 1359–66. http://dx.doi.org/10.1609/aaai.v36i2.20024.

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Features, logits, and labels are the three primary data when a sample passes through a deep neural network. Feature perturbation and label perturbation receive increasing attention in recent years. They have been proven to be useful in various deep learning approaches. For example, (adversarial) feature perturbation can improve the robustness or even generalization capability of learned models. However, limited studies have explicitly explored for the perturbation of logit vectors. This work discusses several existing methods related to logit perturbation. Based on a unified viewpoint between

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Jang, M., J. Choe, and S. J. Kim. "Streamline-based Inversion Model Using Simulated Annealing Coupled with Geostatistical Perturbation Methods." Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 29, no. 14 (2007): 1285–94. http://dx.doi.org/10.1080/15567030600820435.

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Fan, Chuanxin, Xinxiang Tian, and Chunfei Gu. "Perturbation-Based Battery Impedance Characterization Methods: From the Laboratory to Practical Implementation." Batteries 10, no. 12 (2024): 414. http://dx.doi.org/10.3390/batteries10120414.

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To guarantee the secure and effective long-term functionality of lithium-ion batteries, vital functions, including lifespan estimation, condition assessment, and fault identification within battery management systems, are necessary. Battery impedance is a crucial indicator for assessing battery health and longevity, serving as an important reference in battery state evaluation. This study offers a comprehensive review of the characterization and applications of impedance spectroscopy. It highlights the increasing attention paid to broadband perturbation signals for impedance measurements, whic

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Djermoune, E. H., and M. Tomczak. "Perturbation Analysis of Subspace-Based Methods in Estimating a Damped Complex Exponential." IEEE Transactions on Signal Processing 57, no. 11 (2009): 4558–63. http://dx.doi.org/10.1109/tsp.2009.2024030.

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Mo, Wen Hui. "Dynamic Reliability Based on Perturbation Stochastic Finite Element." Applied Mechanics and Materials 155-156 (February 2012): 47–50. http://dx.doi.org/10.4028/www.scientific.net/amm.155-156.47.

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This paper proposes a method of calculating dynamic reliability using perturbation stochastic finite element. Dynamic analysis of perturbation stochastic finite element is introduced and the mean and variance of the stress can be obtained. Samples of stress and strength are generated by computer program. The Monte Carlo simulation is proposed to compute dynamic reliability of structure. Dynamic reliability of structure is computed by the stress-strength interference model. The proposed methods are demonstrated by a numerical example of axle.

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Lakshmi, M. Naga, and Dr K. Sandhya Rani. "PRIVACY PRESERVING CLUSTERING BASED ON SINGULAR VALUE DECOMPOSITION AND GEOMETRIC DATA PERTURBATION." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 10, no. 3 (2013): 1427–33. http://dx.doi.org/10.24297/ijct.v10i3.3272.

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Privacy preservation is a major concern when the application of data mining techniques to large repositories of data consists of personal, sensitive and confidential information. Singular Value Decomposition (SVD) is a matrix factorization method, which can produces perturbed data by efficiently removing unnecessary information for data mining. In this paper two hybrid methods are proposed which takes the advantage of existing techniques SVD and geometric data transformations in order to provide better privacy preservation. Reflection data perturbation and scaling data perturbation are familia

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Huang, Wei, Lei Zhang, Zizhou Wang, and Yan Wang. "GapMatch: Bridging Instance and Model Perturbations for Enhanced Semi-Supervised Medical Image Segmentation." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 16 (2025): 17458–66. https://doi.org/10.1609/aaai.v39i16.33919.

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Medical image segmentation provides detailed understanding and aids in diagnosis, treatment planning, and monitoring of diseases. Due to the high cost of acquiring labeled data in the field of medical image analysis, semi-supervised segmentation methods have garnered increasing attention. Benefiting from their simplicity and effectiveness, consistency regularization-based methods have emerged as a significant research focus by utilizing perturbations. However, existing methods typically consider perturbation strategies from only a single perspective: either instance perturbation or model pertu

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Ouakad, Hassen M., Abdulrahman M. Alofi, and Ali H. Nayfeh. "Dynamic Analysis of Multilayers Based MEMS Resonators." Mathematical Problems in Engineering 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/1262650.

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The dynamic behavior of a microelectromechanical system (MEMS) parallel and electrically coupled double-layers (microbeams) based resonator is investigated. Two numerical methods were used to solve the dynamical problem: the reduced-order modeling (ROM) and the perturbation method. The ROM was derived using the so-called Galerkin expansion with considering the linear undamped mode shapes of straight beam as the basis functions. The perturbation method was generated using the method of multiple scales by direct attack of the equations of motion. Dynamic analyses, assuming the above two numerica

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Grebenikov, E. A. "Concerning New Perturbation Methods in Solar System Dynamics." International Astronomical Union Colloquium 165 (1997): 399–404. http://dx.doi.org/10.1017/s0252921100046868.

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In this paper a new method of construction of the perturbation motion theory of celestial bodies, based on the averaging principle in view of frequency resonances, is stated. The first approximation of the asymptotic theory is the exact solution of the dynamics averaging equations, in which are included “secular” and “long-periodic” terms. The high-degree approximations are the exact solution of a known Krylov-Bogoliubov generalized equation. It is shown that these iterations are expressed in the analytical form by multiple Fourier series.

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Wang, Biao, Xumin Song, Yiyong Li, and Weilin Wang. "A method of satellite constellation observation based on J2 perturbation application." Journal of Physics: Conference Series 2820, no. 1 (2024): 012043. http://dx.doi.org/10.1088/1742-6596/2820/1/012043.

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Abstract In view of the problem of a large number of satellite observations, a method of satellite constellation observation by retrograde orbital spacecraft is proposed by applying the drift of J2 perturbation on the RAAN of the spacecraft. Firstly, the basic configuration and spatial position relationship of the satellite constellation are analyzed. Secondly, the influence of the J2 perturbation on the RAAN of the spacecraft is analyzed. Finally, by using the effect of J2 perturbation, the observation methods of single and multiple retrograde orbit spacecraft for satellite constellation are

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Zhang, Pengcheng, Xiaohan Yu, Xiao Bai, and Jin Zheng. "Visual Perturbation for Text-Based Person Search." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 10 (2025): 10058–66. https://doi.org/10.1609/aaai.v39i10.33091.

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Text-based person search aims at locating a person described by natural language in uncropped scene images. Recent works for TBPS mainly focus on aligning multi-granularity vision and language representations, neglecting a key discrepancy between training and inference where the former learns to unify vision and language features where the visual side covers all clues described by language, yet the latter matches image-text pairs where the images may capture only part of the described clues due to perturbations such as occlusions, background clutters and misaligned boundaries. To alleviate thi

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Wang, Zhengguang. "Validation, Robustness, and Accuracy of Perturbation-Based Sensitivity Analysis Methods for Time-Series Deep Learning Models." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 21 (2024): 23768–70. http://dx.doi.org/10.1609/aaai.v38i21.30559.

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This work undertakes studies to evaluate Interpretability Methods for Time Series Deep Learning. Sensitivity analysis assesses how input changes affect the output, constituting a key component of interpretation. Among the post-hoc interpretation methods such as back-propagation, perturbation, and approximation, my work will investigate perturbation-based sensitivity Analysis methods on modern Transformer models to benchmark their performances. Specifically, my work intends to answer three research questions: 1) Do different sensitivity analysis methods yield comparable outputs and attribute im

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Ratra, Ritu, Preeti Gulia, and Nasib Singh Gill. "Performance analysis of perturbation-based privacy preserving techniques: an experimental perspective." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 5 (2023): 5273. http://dx.doi.org/10.11591/ijece.v13i5.pp5273-5281.

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<span lang="EN-US">Nowadays, enormous amounts of data are produced every second. These data also contain private information from sources including media platforms, the banking sector, finance, healthcare, and criminal histories. Data mining is a method for looking through and analyzing massive volumes of data to find usable information. Preserving personal data during data mining has become difficult, thus privacy-preserving data mining (PPDM) is used to do so. Data perturbation is one of the several tactics used by the PPDM data privacy protection mechanism. In perturbation, datasets a

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Taylor, Zoe, Gregory S. Walsh, Hannah Hawkins, Mario Inacio, and Patrick Esser. "Perturbations during Gait: A Systematic Review of Methodologies and Outcomes." Sensors 22, no. 15 (2022): 5927. http://dx.doi.org/10.3390/s22155927.

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Background: Despite extensive literature regarding laboratory-based balance perturbations, there is no up-to-date systematic review of methods. This systematic review aimed to assess current perturbation methods and outcome variables used to report participant biomechanical responses during walking. Methods: Web of Science, CINAHL, and PubMed online databases were searched, for records from 2015, the last search was on 30th of May 2022. Studies were included where participants were 18+ years, with or without clinical conditions, conducted in non-hospital settings. Reviews were excluded. Partic

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Zhang, Zhiwei, Xunzhang Gao, Shuowei Liu, Bowen Peng, and Yufei Wang. "Energy-Based Adversarial Example Detection for SAR Images." Remote Sensing 14, no. 20 (2022): 5168. http://dx.doi.org/10.3390/rs14205168.

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Adversarial examples (AEs) bring increasing concern on the security of deep-learning-based synthetic aperture radar (SAR) target recognition systems. SAR AEs with perturbation constrained to the vicinity of the target have been recently in the spotlight due to the physical realization prospects. However, current adversarial detection methods generally suffer severe performance degradation against SAR AEs with region-constrained perturbation. To solve this problem, we treated SAR AEs as low-probability samples incompatible with the clean dataset. With the help of energy-based models, we capture

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Fortunati, Alessandro, Diego Misseroni, and Andrea Bacigalupo. "Spectro-hierarchical homogenization scheme for elasto-dynamic problems in periodic Cauchy materials." Applied Mathematical Modelling 132 (July 20, 2024): 366–83. https://doi.org/10.1016/j.apm.2024.04.051.

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The paper introduces a spectro-hierarchical algorithm for approximating solutions to elasto-dynamic problems in periodic heterogeneous materials. This homogenization technique leverages finite-dimensional perturbation theory based on Nekhoroshev’s theorem. The method uses a harmonic hierarchy to construct functions that approximate the solution with a superexponentially small error relative to the cell dimension. The fully homogenized model is connected to the “integrable case” of perturbation theory, with all constants explicitly calculated. Additionally, a threshold for the

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Pan, Christopher S., Sharon Chiou, and Scott Hendricks. "The effect of drywall lifting method on workers' balance in a laboratory-based simulation." Occupational Ergonomics 3, no. 4 (2003): 235–49. http://dx.doi.org/10.3233/oer-2003-3405.

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Voluntary body movement can import a perturbation to the postural stability/balance of a human body. Heavy manual material handling such as drywall lifting may increase this perturbation. The objective of this laboratory-based study was to quantify workers' postural stability while lifting drywall sheets through kinetic and kinematic analyses, and to identify the drywall lifting methods that caused the least perturbation on workers' balance. Sixty male construction workers participated in this study. A simulated drywall-lifting workstation was built and all subjects performed one of the four r

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Krishnarayalu, M. S. "Singular perturbation methods for a class of initial and boundary value problems in multi-parameter classical digital control systems." ANZIAM Journal 46, no. 1 (2004): 67–77. http://dx.doi.org/10.1017/s1446181100013675.

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AbstractA stable linear time-invariant classical digital control system with several widely different small coefficients multiplying the lowest functions is considered. It is formulated as a multi-parameter singularly perturbed system. Perturbation methods are developed for both initial and boundary value problems based on asymptotic expansions of the perturbation parameters. The approximate solution consists of an outer solution and a number of boundary layer correction solutions equal to the number of initial conditions lost in the process of degeneration. An example is provided for illustra

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Kuić, Domagoj, Alemka Knapp, and Diana Šaponja-Milutinović. "Finite Time Path Field Theory Perturbative Methods for Local Quantum Spin Chain Quenches." Universe 10, no. 10 (2024): 384. http://dx.doi.org/10.3390/universe10100384.

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We discuss local magnetic field quenches using perturbative methods of finite time path field theory (FTPFT) in the following spin chains: Ising and XY in a transverse magnetic field. Their common characteristics are: (i) they are integrable via mapping to a second quantized noninteracting fermion problem; and (ii) when the ground state is nondegenerate (true for finite chains except in special cases), it can be represented as a vacuum of Bogoliubov fermions. By switching on a local magnetic field perturbation at finite time, the problem becomes nonintegrable and must be approached via numeric

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DOUGLAS, JIM, and SEONGJAI KIM. "IMPROVED ACCURACY FOR LOCALLY ONE-DIMENSIONAL METHODS FOR PARABOLIC EQUATIONS." Mathematical Models and Methods in Applied Sciences 11, no. 09 (2001): 1563–79. http://dx.doi.org/10.1142/s0218202501001471.

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Classical alternating direction (AD) and fractional step (FS) methods for parabolic equations, based on some standard implicit time-stepping procedure such as Crank–Nicolson, can have errors associated with the AD or FS perturbations that are much larger than the errors associated with the underlying time-stepping procedure. We show that minor modifications in the AD and FS procedures can virtually eliminate the perturbation errors at an additional computational cost that is less than 10% of the cost of the original AD or FS method. Moreover, after these modifications, the AD and FS procedures

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Ning, W., and L. He. "Computation of Unsteady Flows Around Oscillating Blades Using Linear and Nonlinear Harmonic Euler Methods." Journal of Turbomachinery 120, no. 3 (1998): 508–14. http://dx.doi.org/10.1115/1.2841747.

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A quasi-three-dimensional time-linearized Euler method has been developed to compute unsteady flows around oscillating blades. In the baseline method, unsteady flow is decomposed into a steady flow plus a linear harmonically varying unsteady flow. Both the steady flow equations and the unsteady perturbation equations are solved using a pseudo-time-marching method. Based upon this method, a novel nonlinear harmonic Euler method has been developed. Due to the nonlinearity of the aerodynamic governing equations, time-averaging generates extra “unsteady stress” terms. These nonlinear effects are i

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Asmolovskiy, Nikolay, Anton Tkachuk, and Manfred Bischoff. "Numerical approaches to stability analysis of cylindrical composite shells based on load imperfections." Engineering Computations 32, no. 2 (2015): 498–518. http://dx.doi.org/10.1108/ec-10-2013-0246.

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Purpose – Current procedures of buckling load estimation for thin-walled structures may provide very conservative estimates. Their refinement offers the potential to use structure and material properties more efficiently. Due to the large variety of design variables, for example laminate layup in composite structures, a prohibitively large number of tests would be required for experimental assessment, and thus reliable numerical techniques are of particular interest. The purpose of this paper is to analyze different methods of numerical buckling load estimation, formulate simulation procedures

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Jin, Rubo, Jianda Cheng, Wei Wang, Huiqiang Zhang, and Jun Zhang. "Attribute Feature Perturbation-Based Augmentation of SAR Target Data." Sensors 24, no. 15 (2024): 5006. http://dx.doi.org/10.3390/s24155006.

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Large-scale, diverse, and high-quality data are the basis and key to achieving a good generalization of target detection and recognition algorithms based on deep learning. However, the existing methods for the intelligent augmentation of synthetic aperture radar (SAR) images are confronted with several issues, including training instability, inferior image quality, lack of physical interpretability, etc. To solve the above problems, this paper proposes a feature-level SAR target-data augmentation method. First, an enhanced capsule neural network (CapsNet) is proposed and employed for feature e

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Montazeri-Gh, Morteza, and Ali Rasti. "Analyzing different numerical linearization methods for the dynamic model of a turbofan engine." Mechanics & Industry 20, no. 3 (2019): 303. http://dx.doi.org/10.1051/meca/2019012.

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State equations of aircraft engine dynamics usually required for controller design, are not available in closed form, so the dynamic models are commonly linearized numerically. Development of model-based controllers for aeroengine in the recent years necessitates the use of accurate linear models. However, there is no comprehensive study about the accuracy of the linear models obtained from nonlinear engine models. In this paper, the accuracy of different numerical linearization methods for linearizing the dynamic model of a turbofan engine is investigated. For this objective, a thermodynamic

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Khidir, Ahmed A. "A New Spectral-Homotopy Perturbation Method and Its Application to Jeffery-Hamel Nanofluid Flow with High Magnetic Field." Journal of Computational Methods in Physics 2013 (December 30, 2013): 1–10. http://dx.doi.org/10.1155/2013/939143.

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We present a new modification of the homotopy perturbation method (HPM) for solving nonlinear boundary value problems. The technique is based on the standard homotopy perturbation method, and blending of the Chebyshev pseudospectral methods. The implementation of the new approach is demonstrated by solving the Jeffery-Hamel flow considering the effects of magnetic field and nanoparticle. Comparisons are made between the proposed technique, the standard homotopy perturbation method, and the numerical solutions to demonstrate the applicability, validity, and high accuracy of the present approach

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Wang, Xiangyu, Song Cen, and Chenfeng Li. "Generalized Neumann Expansion and Its Application in Stochastic Finite Element Methods." Mathematical Problems in Engineering 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/325025.

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An acceleration technique, termed generalized Neumann expansion (GNE), is presented for evaluating the responses of uncertain systems. The GNE method, which solves stochastic linear algebraic equations arising in stochastic finite element analysis, is easy to implement and is of high efficiency. The convergence condition of the new method is studied, and a rigorous error estimator is proposed to evaluate the upper bound of the relative error of a given GNE solution. It is found that the third-order GNE solution is sufficient to achieve a good accuracy even when the variation of the source stoc

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Chai, Yu, and Dong Mei Shang. "The Improvement of Maximum Power Point Tracker Algorithm in Photovoltaic Power System." Applied Mechanics and Materials 157-158 (February 2012): 377–80. http://dx.doi.org/10.4028/www.scientific.net/amm.157-158.377.

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Maximum power tracking is one of most important methods to improve efficiency of Photovoltaic power system. By simulating and analyzing the photovoltaic cell model，using Boost circuit to achieve maximum power tracking. Based on the analysis of the constant-voltage method, perturbation and observation method, then combining these two methods，I Put forward the constant-voltage method combined with perturbation and observation method, and has carried on the simulation.

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Yin, Hui, Dejie Yu, Shengwen Yin, and Baizhan Xia. "Efficient Midfrequency Analysis of Built-Up Structure Systems with Interval Parameters." Shock and Vibration 2015 (2015): 1–18. http://dx.doi.org/10.1155/2015/712428.

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To improve the efficiency of midfrequency analysis of built-up structure systems with interval parameters, the second-order interval and subinterval perturbation methods are introduced into the hybrid finite element/statistical energy analysis (FE/SEA) framework in this paper. Based on the FE/SEA for built-up structure systems and the second-order interval perturbation method, the response variables are expanded with the second-order Taylor series and nondiagonal elements of the Hessian matrices are neglected. Extreme values of the expanded variables are searched by using efficient search algo

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Ferreira, Rafael N., Nuno Ferrete Ribeiro, Joana Figueiredo, and Cristina P. Santos. "Provoking Artificial Slips and Trips towards Perturbation-Based Balance Training: A Narrative Review." Sensors 22, no. 23 (2022): 9254. http://dx.doi.org/10.3390/s22239254.

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Humans’ balance recovery responses to gait perturbations are negatively impacted with ageing. Slip and trip events, the main causes preceding falls during walking, are likely to produce severe injuries in older adults. While traditional exercise-based interventions produce inconsistent results in reducing patients’ fall rates, perturbation-based balance training (PBT) emerges as a promising task-specific solution towards fall prevention. PBT improves patients’ reactive stability and fall-resisting skills through the delivery of unexpected balance perturbations. The adopted perturbation conditi

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Zhang, Qinglong, Lu Rao, and Yubin Yang. "A Novel Visual Interpretability for Deep Neural Networks by Optimizing Activation Maps with Perturbation." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 4 (2021): 3377–84. http://dx.doi.org/10.1609/aaai.v35i4.16450.

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Interpretability has been regarded as an essential component for deploying deep neural networks, in which the saliency-based method is one of the most prevailing interpretable approaches since it can generate individually intuitive heatmaps that highlight parts of the input image that are most important to the decision of the deep networks on a particular classification target. However, heatmaps generated by existing methods either contain little information to represent objects (perturbation-based methods) or cannot effectively locate multi-class objects (activation-based approaches). To addr

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Duan, Jiale, Linyao Qiu, Guangjun He, Ling Zhao, Zhenshi Zhang, and Haifeng Li. "A Region-Adaptive Local Perturbation-Based Method for Generating Adversarial Examples in Synthetic Aperture Radar Object Detection." Remote Sensing 16, no. 6 (2024): 997. http://dx.doi.org/10.3390/rs16060997.

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In synthetic aperture radar (SAR) imaging, intelligent object detection methods are facing significant challenges in terms of model robustness and application security, which are posed by adversarial examples. The existing adversarial example generation methods for SAR object detection can be divided into two main types: global perturbation attacks and local perturbation attacks. Due to the dynamic changes and irregular spatial distribution of SAR coherent speckle backgrounds, the attack effectiveness of global perturbation attacks is significantly reduced by coherent speckle. In contrast, by

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Che, Lei, Chengcong Wu, and Yan Hou. "Large Language Model Text Adversarial Defense Method Based on Disturbance Detection and Error Correction." Electronics 14, no. 11 (2025): 2267. https://doi.org/10.3390/electronics14112267.

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This study aims to effectively defend against complex and diverse adversarial attacks, enhance adversarial defense performance in the field of textual adversarial examples, and address existing issues in current defense methods such as models’ inability to accurately detect perturbations and perform effective error correction. To this end, we propose a Large Language Model Adversarial Defense (LLMAD) method based on perturbation detection and correction. The LLMAD framework consists of two modules: a perturbation detection module and a perturbation correction module. The detection module combi

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Jeong, Soyeong, Pilwon Kim, and Chang Hyeong Lee. "Perturbation and Truncation of Probability Generating Function Methods for Stiff Chemical Reactions." Journal of Applied Mathematics 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/864238.

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One can reformulate chemical master equations of the stochastic reaction network into a partial differential equation (PDE) of a probability generating function (PGF). In this paper, we present two improvements in such PGF-PDE approach, based on perturbation and double-truncation, respectively. The stiff system that involves fast and slow reactions together often requires high computational cost. By applying the perturbation method to PGF-PDEs, we expand the equation in terms of a small reaction rate which is often responsible for such stiffness of the system. Also by doubly truncating, we dum

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Deng, Zhiyang, Shilin Wei, Tao Chen, Xiaochun Song, and Yihua Kang. "A wall-thinning measuring method based on magnetic permeability perturbation." International Journal of Applied Electromagnetics and Mechanics 64, no. 1-4 (2020): 921–30. http://dx.doi.org/10.3233/jae-209406.

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In the determination of metal thickness by traditional electromagnetic nondestructive testing methods, the material’s electrical conductivity and magnetic permeability are required but practically unavailable or inexact. In this paper, a wall-thinning measuring method based on magnetic permeability variation of steel pipes is proposed. The direct current magnetization is applied to the ferromagnetic material, the internal magnetic field perturbation caused by the wall-thinning brings the permeability perturbation in the surface layer and be sensed by eddy current probe. The simulation results

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Gottu Mukkula, Anwesh Reddy, and Sebastian Engell. "Handling Measurement Delay in Iterative Real-Time Optimization Methods." Processes 9, no. 10 (2021): 1800. http://dx.doi.org/10.3390/pr9101800.

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This paper is concerned with the real-time optimization (RTO) of chemical plants, i.e., the optimization of the steady-state operating points during operation, based on inaccurate models. Specifically, modifier adaptation is employed to cope with the plant-model mismatch, which corrects the plant model and the constraint functions by bias and gradient correction terms that are computed from measured variables at the steady-states of the plant. This implies that the sampling time of the iterative RTO scheme is lower-bounded by the time to reach a new steady-state after the previously computed i

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