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DIGITAL-CONTROL OF LOCAL SOUND FIELDS IN AN AIRCRAFT PASSENGER COMPARTMENT

AIAA JOURNAL 1990年第2期28卷 284-289页

作者： WARNER, JV BERNHARD, RJ PURDUE UNIV SCH MECH ENGNW LAFAYETTEIN 47907

Active noise control has been shown to be a promising solution for reducing noise levels in turboprop aircraft. The first part of this paper shows the performance of a broadband active noise control system based upon an off-line frequency domain model obtained from system response measurements. A laboratory test in an 18 passenger airplane fuselage resulted in 10-20 dB reduction of broadband deterministic noise over a substantial frequency range. However, the sensitivity of the system to environmental changes made clear the impracticality of using off-line modeling techniques. Thus the paper addresses the use of adaptive digital filtering techniques for active noise control in aircraft. Results are presented from a simulation study in which the Least Mean Square (LMS) and recursive Least Mean Square (RLMS) gradient search techniques are used to model actual system response measurements. The LMS and RLMS algorithms were found to be equally capable of modeling the airplane system. However, for a dense harmonic sound field, the LMS estimator was superior, attenuating most harmonics by more than 30 dB, whereas the RLMS estimator reduced most harmonics by 20 dB. © 1990 American Institute of Aeronautics and Astronautics, Inc., All rights reserved.

关键词： Commercial Aircraft Open Loop Controller Frequency Response Functions Adaptive Filter Turbofan Engines Fuselages Microprocessors recursive algorithm Propulsion System Structural Members

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A recursive Least Squares Error Method Aided by Variable-Windowed Short-Time Discrete Fourier Transform for Frequency Tracking in Smart Grid

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2015年第2期E98A卷 721-734页

作者： Li, Hui Yuan, Liang Hainan Univ Coll Informat Sci & Technol Haikou 520287 Peoples R China Zhejiang Univ Sch Aeronaut & Astronaut Hangzhou 310027 Zhejiang Peoples R China Haisum Engn CO LTD Shanghai 200031 Peoples R China

Least squares error (LSE) method adopted recursively can be used to track the frequency and amplitude of signals in steady states and kinds of non-steady ones in power system. Taylor expansion is used to give another version of this recursive LSE method. Aided by variable-windowed short-time discrete Fourier transform, recursive LSEs with and without Taylor expansion converge faster than the original ones in the circumstance of off-nominal input singles. Different versions of recursive LSE were analyzed under various states, such as signals of off-nominal frequency with harmonics, signals with step changes, signals modulated by a sine signal, signals with decaying DC offset and additive Gaussian white noise. Sampling rate and data window size are two main factors influencing the performance of method recursive LSE in transient states. recursive LSE is sensitive to step changes of signals, but it is in-sensitive to signals' modulation and singles with decaying DC offset and noise.

关键词： smart grid frequency tracking recursive algorithm least squares error short-time discrete Fourier transform variable window

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An efficient learning algorithm for improving generalization performance of radial basis function neural networks

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NEURAL NETWORKS 2000年第4-5期13卷 545-553页

作者： Wang, ZO Zhu, T Tianjin Univ Inst Syst Engn Tianjin 300072 Peoples R China

This paper presents an efficient recursive learning algorithm for improving generalization performance of radial basis function (RBF) neural networks. The approach combines the rival penalized competitive learning (PRCL) [Xu, L., Kizyzak, A. & Oja, E. (1993). Rival penalized competitive learning for clustering analysis, RBF net and curve detection, IEEE Transactions on Neural Networks, 4, 636-649] and the regularized least squares (RLS) to provide an efficient and powerful procedure for constructing a minimal RBF network that generalizes very well. The RPCL selects the number of hidden units of network and adjusts centers, while the RLS constructs the parsimonious network and estimates the connection weights. In the RLS we derived a simple recursive algorithm, which needs no matrix calculation, and so largely reduces the computational cost. This combined algorithm significantly enhances the generalization performance and the real-time capability of the RBF networks. Simulation results of three different problems demonstrate much better generalization performance of the present algorithm over other existing similar algorithms. (C) 2000 Elsevier Science Ltd. All rights reserved.

关键词： radial basis function neural network generalization performance rival penalized competitive learning regularized least squares recursive algorithm real-time capability

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Adaptive kernel principal component analysis

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SIGNAL PROCESSING 2010年第5期90卷 1542-1553页

作者： Ding, Mingtao Tian, Zheng Xu, Haixia Northwestern Polytech Univ Sch Sci Xian 710129 Peoples R China Northwestern Polytech Univ Dept Comp Sci & Engn Xian 710129 Peoples R China Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing Applicat Beijing 100101 Peoples R China

An adaptive kernel principal component analysis (AKPCA) method, which has the flexibility to accurately track the kernel principal components (KPC), is presented. The contribution of this paper may be divided into two parts. First, KPC are recursively formulated to overcome the batch nature of standard kernel principal component analysis (KPCA). This formulation is derived from the recursive eigendecomposition of kernel covariance matrix and indicates the KPC variation caused by the new data. Second, kernel covariance matrix is correctly updated to adapt to the changing characteristics of data. In this adaptive method, the KPC is adaptively adjusted without re-eigendecomposing the kernel Gram matrix. The proposed method not only maintains constant update speed and memory usage as the data-size increases, but also alleviates sub-optimality of the KPCA method for non-stationary data. Experiments for simulation data and real applications are detailed to assess the utility of the proposed method. The results demonstrate that our approach yields improvements in terms of both computational speed and approximation accuracy. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

关键词： Adaptive method Kernel principal component analysis Kernel principal component Non-stationary data recursive algorithm

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Application of the Kalman filter to the Nash model

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HYDROLOGICAL PROCESSES 1998年第5期12卷 755-767页

作者： Lee, YH Singh, VP Kyungsan Univ Dept Environm Sci Kyungsan 712715 South Korea

The Nash model was used for application of the Kalman filter. The state vector of the rainfall-runoff system was constituted by the IUH (instantaneous unit hydrograph) estimated by the Nash model and the runoff estimated by the Nash model using the Kalman filter. The initial values of the state vector were assumed as the average of 10% of the IUH peak values and the initial runoff estimated from the average IUH. The Nash model using the Kalman filter with a recursive algorithm accurately predicted runoff from a basin in Korea. The filter allowed the IUH to vary in time, increased the accuracy of the Nash model and reduced physical uncertainty of the rainfall-runoff process in the river basin. (C) 1998 John Wiley & Sons, Ltd.

关键词： Kalman filter Nash model IUH rainfall-runoff system system model measurement model Kalman gain state estimation error measurement error recursive algorithm

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Low-complexity search for optimal delay in linear FIR MMSE equalization

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IEEE SIGNAL PROCESSING LETTERS 2005年第8期12卷 549-552页

作者： Szczecinski, L Inst Natl Rech Sci EMT Montreal PQ H5A 1K6 Canada

In this letter, an efficient algorithm to determine the optimal delay in linear finite impulse response equalizers based on the minimum mean-square-error criterion is proposed. The algorithm uses the Levinson-Durbin (L-D) recursion as a starting point to find the values of the mean-square error for equalizers with all nontrivial delays. Despite the exhaustive search approach, the complexity of the proposed algorithm is only doubled when compared to the calculation of the equalizer with one prescribed delay. Such increase in complexity may be fully justified in practice because it yields globally optimal equalizer's design.

关键词： equalization equalization delay fast algorithm finite impulse response (FIR) equalization Levinson-Durbin (L-D) algorithm minimum mean-square-error (MMSE) equalization optimal delay recursive algorithm

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Identification of linear continuous-time systems under irregular and random output sampling

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AUTOMATICA 2015年 60卷 100-114页

作者： Mu, Biqiang Guo, Jin Wang, Le Yi Yin, George Xu, Lijian Zheng, Wei Xing Chinese Acad Sci Acad Math & Syst Sci Inst Syst Sci Key Lab Syst & Control Being 100190 Peoples R China Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Wayne State Univ Dept Elect & Comp Engn Detroit MI 48202 USA Wayne State Univ Dept Math Detroit MI 48202 USA SUNY Farmingdale State Coll Dept Elect & Comp Engn Technol Farmingdale NY 11735 USA Univ Western Sydney Sch Comp Engn & Math Sydney NSW 2751 Australia

This paper considers the problem of identifiability and parameter estimation of single-input-single-output, linear, time-invariant, stable, continuous-time systems under irregular and random sampling schemes. Conditions for system identifiability are established under inputs of exponential polynomial types and a tight bound on sampling density. Identification algorithms of Gauss-Newton iterative types are developed to generate convergent estimates. When the sampled output is corrupted by observation noises, input design, sampling times, and convergent algorithms are intertwined. Persistent excitation (PE) conditions for strongly convergent algorithms are derived. Unlike the traditional identification, the PE conditions under irregular and random sampling involve both sampling times and input values. Under the given PE conditions, iterative and recursive algorithms are developed to estimate the original continuous-time system parameters. The corresponding convergence results are obtained. Several simulation examples are provided to verify the theoretical results. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Linear continuous-time system Irregular and random sampling Identifiability Iterative algorithm recursive algorithm Strong consistency Asymptotical normality

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Improved algorithm for electromagnetic scattering of plane waves by a radially stratified tilted cylinder and its application

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OPTICS COMMUNICATIONS 2006年第1期266卷 13-18页

作者： Jiang Huifen Han Xiang'e Li Renxian Xidian Univ Sch Sci Xian Peoples R China

An efficient numerical procedure for computing the scattering coefficients of a radially stratified tilted cylinder is discussed. Compared with the previous algorithms, computations for scattering field in our code are extended to fairly large parameters, up to more than 10,000 and a few millions in number of layers, and computational time is only a few seconds. The capabilities of our code depend also on the memory of computer. The algorithm can also be used for absorbing or nonabsorbing cylinders in different electromagnetic wave bands. Compared with the known results, the algorithm is validated. At last, the algorithm is used to simulate the intensity distributions of two-layered cylinders with large size parameter and of graded-index polymer optical fiber (GI-POF) at tilted incidence, which supplies information on non-intrusive measurement on-line of refractive index profile by light scattering. (c) 2006 Elsevier B.V. All rights reserved.

关键词： particle sizing electromagnetic scattering tilted infinite multilayered cylinder recursive algorithm

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A comparison design of comb decimators for sigma-delta analog-to-digital converters

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ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING 2000年第1期22卷 51-60页

作者： Gao, YH Jia, LH Isoaho, J Tenhunen, H Royal Inst Technol Elect Syst Design Lab S-16440 Stockholm Sweden

This paper presents a comparison design of comb decimators based on the non-recursive algorithm and the recursive algorithm. Compared with the recursive algorithm, the main advantage of the non-recursive algorithm is its abilities of reducing power consumption and increasing circuit speed especially when the decimation ratio and filter order are high. Based on the non-recursive algorithm, a decimator with programmable filter orders (3rd, 4th and 5th), decimation ratios (8, 16, 32 and 64) and input bits (1 and 2 bits) has been implemented in a 0.6 mu m 3.3 V CMOS process. Its measured core power consumption is 44 mW at the oversampling rate of 25 MHz and its highest input data rate is 110 MHz.

关键词： comb decimator non-recursive algorithm recursive algorithm low power high speed sigma-delta A/D converters

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Q-Method Extended Kalman Filter

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2015年第4期38卷 752-760页

作者： Ainscough, Thomas Zanetti, Renato Christian, John Spanos, Pol D. Rice Univ US Air Force Charles Stark Draper Lab Houston TX 77058 USA Charles Stark Draper Lab Houston TX 77058 USA W Virginia Univ Dept Mech & Aerosp Engn Morgantown WV 26508 USA Rice Univ Ryon Chair Engn Houston TX 77005 USA

A new algorithm is proposed that smoothly incorporates the nonlinear estimation of the attitude quaternion using Davenport's q-method and the estimation of nonattitude states through an extended Kalman filter. The new algorithm is compared to an existing one and the various similarities and differences are discussed. The validity of the proposed approach is confirmed by numerical simulations.

关键词： Extended Kalman Filter Singular Value Decomposition Numerical Simulation Taylor Series Magnetometers Earth Monte Carlo Simulation Newton Raphson Method Gaussian White Noise recursive algorithm

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