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Research on Invalid Detection Data Model of Mine Catalytic Sensors Based on Machine Learning

IEEE SENSORS JOURNAL 2023年第3期23卷 1925-1932页

作者： Bowen, Wang China Coal Technol Engn Grp Chongqing Res Chongqing 400030 Peoples R China

In order to solve the problem of nonlinear failure data output by the catalytic combustible sensor (later referred as a sensor) when working in the mine environment, this article proposes a backpropagation (BP) neural network nonlinear data filtering model based on the Levenberg-Marquardt (L-M) algorithm. The experimental analysis shows that this model has obvious advantages in training speed and error performance compared with the BP neural network model established by a quasi-newton algorithm and adaptive linear regression (lr) momentum gradient descent algorithm. In terms of generalization ability, this model has better generalization ability than the radial basis function (RBF) feedforward neural network model with K -means clustering. Based on the above advantages, the model can effectively filter the sensor failure output data, eliminate the hidden danger of safety production caused by the failure output data, and improve the level of safety production in coal mines.

关键词： Gas detectors Sensor phenomena and characterization Biological neural networks Sensor systems Methane Resistance Data models Catalytic sensor backpropagation (BP) neural network combustible gas sensor Levenberg-Marquardt (L-M) algorithm machine learning neural network quasi-newton algorithm radial basis function (RBF) neural network

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A new quasi-newton pattern search method based on symmetric rank-one update for unconstrained optimization

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COMPUTERS & MATHEMATICS WITH APPLICATIONS 2008年第6期55卷 1201-1214页

作者： Wu, Ting Sun, Linping Nanjing Univ Dept Math Nanjing 210093 Peoples R China

This paper proposes a new robust and quickly convergent pattern search method based on an implementation of OCSSRI (Optimal Conditioning Based Self-Scaling Symmetric Rank-One) algorithm [M.R. Osborne, L.P. Sun, A new approach to symmetric rank-one Updating, IMA Journal of Numerical Analysis 19 (1999) 497-507] for Unconstrained optimization. This method Utilizes the factorization of approximating Hessian matrices to provide a series of convergent positive bases needed in pattern search process. Numerical experiments on some famous optimization test problems show that the new method performs well and is competitive in comparison with some other derivative-free methods. (C) 2007 Elsevier Ltd. All rights reserved.

关键词： pattern search positive basis quasi-newton algorithm SRI update derivative-free optimization

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Efficient Attributed Scatter Center Extraction Based on Image-Domain Sparse Representation

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2020年 68卷 4368-4381页

作者： Yang, Dongwen Ni, Wei Du, Lan Liu, Hongwei Wang, Jiadong Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China CSIRO Data61 Sydney NSW 2122 Australia

As an efficient way to interpret the measurements of high-frequency synthetic aperture radar (SAR), an attributed scattering center (ASC) model provides concise and physically relevant features of complex targets. However, accurate extractions of ASCs have been heavily penalized by high memory requirements and computational complexity. We propose to convert SAR measurements to sparse representations in the image domain where the ASC model parameters can be estimated by using an orthogonal matching pursuit (OMP) algorithm or its newtonlized variation. Two important new properties of the ASC model are unveiled in the image domain, namely, "translatability" and "additivity." The properties can help save the dictionary of OMP from sampling the position and length parameters. The atoms of the dictionary become localized, thereby reducing the dictionary size and accelerating ASC extractions. Extensive experiments are conducted based on open-source XPATCH Backhoe data, measured MSTAR data, and synthetic backscatter data. The results show that the proposed approach is able to outperform existing image-domain algorithms in terms of accuracy and noise resistance, and outperform existing frequency-domain algorithms in terms of memory requirement and runtime.

关键词： Signal processing algorithms Scattering Frequency-domain analysis Matching pursuit algorithms Dictionaries Synthetic aperture radar Computational modeling Synthetic aperture radar (SAR) image attributed scattering model (ASM) orthogonal matching pursuit (OMP) quasi-newton algorithm

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Channel estimation in ECMA-368-based UWB systems with unknown interference

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TELECOMMUNICATION SYSTEMS 2013年第2期52卷 1159-1169页

作者： Islam, S. M. Riazul Ameen, M. A. Kwak, Kyung Sup Inha Univ Telecommun Engn Lab Inchon 402751 South Korea

Ultra-wideband (UWB) is one of the fledging paradigms that the next generation of wireless personal area network (WPAN) is developing towards. With its appealing dimensions, UWB communication comes with a set of challenges of which channel estimation is prominent. In this article, we explore the problem of channel estimation in ECMA-368-based multiband orthogonal frequency division multiplexing (MB-OFDM) UWB system affected by unknown narrowband interference (NBI). We analytically show that the unknown NBI causes larger variance of a channel estimator. Thus, MB-OFDM UWB systems are supposed to experience significant performance degradation. To reduce this effect, we follow a new preamble-based channel estimation approach, where the interference power on each subcarrier is treated as a nuisance parameter which is averaged out from the corresponding likelihood function. The later is then optimized in an iterative manner according to the quasi-newton algorithm. Furthermore, we address highly-accurate channel estimation in a time-variant channel and propose an iterative interpolation method. Simulation results indicate that our proposed approaches provide more precise estimation performances than those offered by conventional channel estimation methods.

关键词： Ultra-wideband (UWB) MB-OFDM Channel estimation Maximum likelihood (ML) quasi-newton algorithm Iterative interpolation

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A Variable Step-Size Regularization-Based quasi-newton Adaptive Filter for System Identification

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IEEE ACCESS 2024年 12卷 10059-10068页

作者： Bekrani, Mehdi Zayyani, Hadi Qom Univ Technol Fac Elect & Comp Engn Qom Iran

The family of least mean square (LMS) based adaptive filtering algorithms suffers from convergence performance limitation due to the sensitivity of such algorithms to the eigenvalue spread of the input correlation matrix. The quasi-newton family of adaptive filtering algorithms addresses this limitation, but its performance is restricted by the estimation accuracy of the correlation matrix inverse, especially for highly correlated input signals. Furthermore, the convergence rate and the steady-state performance of both LMS and quasi-newton families are thoroughly depending on their step-sizes. In this paper, a variable step-size regularized quasi-newton adaptive algorithm is proposed in the context of system identification. In this algorithm, inspired by the matrix inversion lemma, a modified regularized matrix inverse with a time-varying regularization is computed such that during the convergence, the contribution of matrix inverse in the weight update is reduced, resulting in a more noise-robust algorithm. The paper further provides a convergence analysis of the proposed quasi-newton algorithm, wherein a variable step-size is proposed to achieve a high initial convergence rate and a low steady-state error in the context of system identification applications.

关键词： Adaptive filter quasi-newton algorithm regularization system identification variable step-size

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Weighted Minimization of Roundoff Noise and Pole Sensitivity Subject to l2-Scaling Constraints for State-Space Digital Filters

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2019年第11期E102A卷 1473-1480页

作者： Hinamoto, Yoichi Doi, Akimitsu NIT Kagawa Coll Dept Elect & Comp Engn Takamatsu Kagawa 7618058 Japan Hiroshima Inst Technol Fac Appl Informat Sci Hiroshima 7315193 Japan

This paper deals with the problem of minimizing roundoff noise and pole sensitivity simultaneously subject to l(2)-scaling constraints for state-space digital filters. A novel measure for evaluating roundoff noise and pole sensitivity is proposed, and an efficient technique for minimizing this measure by jointly optimizing state-space realization and error feedback is explored, namely, the constrained optimization problem at hand is converted into an unconstrained problem and then the resultant problem is solved by employing a quasi-newton algorithm. A numerical example is presented to demonstrate the validity and effectiveness of the proposed technique.

关键词： error feedback l(2)-scaling pole sensitivity quasi-newton algorithm roundoff noise state-space digital filter

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A piecewise line-search technique for maintaining the positive definitenes of the matrices in the SQP method

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2000年第2期16卷 121-158页

作者： Armand, P Gilbert, JC Dept Math LACO CNRS ESA 6090 F-87060 Limoges France INRIA Rocquencourt F-78153 Le Chesnay France

A technique for maintaining the positive definiteness of the matrices in the quasi-newton version of the SQP algorithm is proposed. In our algorithm, matrices approximating the Hessian of the augmented Lagrangian are updated. The positive definiteness of these matrices in the space tangent to the constraint manifold is ensured by a so-called piecewise line-search technique, while their positive definiteness in a complementary subspace is obtained by setting the augmentation parameter. In our experiment, the combination of these two ideas leads to a new algorithm that turns out to be more robust and often improves the results obtained with other approaches.

关键词： BFGS formula equality constrained optimization piecewise line-search quasi-newton algorithm successive quadratic programming

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Parameter identification in multistage population dynamics model

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NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS 2011年第6期12卷 3315-3328页

作者： Picart, Delphine Ainseba, Bedr'eddine Arizona State Univ Sch Math & Stat Sci Tempe AZ 85287 USA Bordeaux Univ IMB UMR CNRS 5251 Anubis Team INRIA Bordeaux Sud Ouest F-33076 Bordeaux France

We present a numerical analysis to solve a parameter identification problem. We identify the demographical parameters of a multistage population dynamics model (Ainseba et al., 2011 [12]). Our nonlinear optimization problem with constraints is solved by a quasi-newton method. The convergence proof of this numerical method is performed here. Some numerical applications of it are also given at the end of the paper. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Population dynamics Age-structured model Parameter estimation Experimental data Lagrangian quasi-newton algorithm

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Optimal control of cylinder wakes via suction and blowing

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COMPUTERS & FLUIDS 2003年第2期32卷 149-171页

作者： Li, ZJ Navon, IM Hussaini, MY Le Dimet, FX Florida State Univ Sch Comp Sci & Informat Technol Tallahassee FL 32306 USA Florida State Univ Dept Math Tallahassee FL 32306 USA Univ Grenoble 1 Lab Modelizat & Calcul Grenoble 9 France

A general method based on adjoint formulation is discussed for the optimal control of distributed parameter systems (including boundary parameter) which is especially suitable for large dimensional control problems. Strategies for efficient and robust implementation of the method are described. The method is applied to the problem of controlling vortex shedding behind a cylinder (through suction/blowing on the cylinder surface) governed by the unsteady two-dimensional incompressible Navier-Stokes equations space discretized by finite-volume approximation with time-dependent boundary conditions. Three types of objective functions are considered, with regularization to circumvent ill-posedness. These objective functions involve integration over a space-time domain. The minimization of the cost function uses a quasi-newton DFP method. A complete control of vortex shedding is demonstrated for Reynolds numbers up to 110. The optimal values of the suction/blowing parameters are found to be insensitive to initial conditions of the model when the time window of control is larger than the vortex shedding period, the inverse of the Strouhal frequency. Although this condition is necessary for robust control, it is observed that a shorter window of control may suffice to suppress vortex shedding. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： optimal control flow control coding adjoint model quasi-newton algorithm regularization Navier-Stokes equations Karman vortex shedding

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A New Approach for Sparse Signal Recovery in Compressed Sensing Based on Minimizing Composite Trigonometric Function

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IEEE ACCESS 2018年 6卷 44894-44904页

作者： Zhang, Chunjie Hao, Dongbin Hou, Changbo Yin, Xiangjun Harbin Engn Univ Coll Informat & Commun Engn Harbin 150001 Heilongjiang Peoples R China

Accurate signal recovery from an underdetermined system of linear equation (USLE) is a topic of considerable interest;such as compressed sensing (CS), recovery of low-rank matrix, blind source separation, and related fields. In order to improve the accuracy of signal recovery from an USLE in CS, we develop a new algorithm called composite trigonometric function null-space re-weighted approximate l(0)-norm (CTNRAL0). The proposed algorithm deploys composite trigonometric function as a nonconvex penalty for sparsity which can better approximate l(0)-norm and can yield more accurate solution. To solve nonconvex minimization formulation efficiently, we adopt a gradual nonconvexity method. In addition, the null space measurement matrix is applied in the CTNRAL0 algorithm, which reduces the dimension of the matrix. The proposed algorithm has been compared with the smoothed l(0)-norm and null-space re-weighted approximate l(0)-norm algorithm via numerical simulations to show its improved performance in the noise environment, while computation cost required is comparable. Furthermore, compared with the interior-point LP solvers and iteratively re-weighted least squares algorithm, the proposed algorithm computation cost can reduce by 1 or 2 orders of magnitude.

关键词： Composite trigonometric function iteratively re-weighted method null-space of the measurement matrix quasi-newton algorithm smooth approximations of non-smooth functions unconstrained convex optimization

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