A gradient-free adaptation method for nonlinear active noise control

Active Noise Control (ANC) problems are often affected by nonlinear effects, such as saturation and distortion of microphones and loudspeakers. Nonlinear models and specific adaptation algorithms must be employed to properly account for these effects. The nonlinear structure of the problem complicates the application of gradient-based Least Mean Squares (LMS) algorithms, due to the fact that exact gradient calculation requires executing nonlinear recursive filtering operations, which pose computational and stability issues. One favored solution to this problem consists in neglecting recursive terms in the gradient calculation, an approximation which is not always without consequences on the convergence performance. Besides, an efficient application of nonlinear models cannot avoid some form of model structure selection, to avoid the well-known effects of overparametrization and to reduce the computational load on-line. Unfortunately, the standard ANC setting configures an indirect identification problem, due to the presence of the secondary path in the control loop. In the nonlinear case, this destroys the linear regression structure of the problem even if the control filter is linear-in-the-parameters, thereby making it impossible to apply the many existing model selection methods for linear regression problems. A simple and computationally wise low demanding approach is here proposed for parameter estimation and model structure selection that provides an answer to the mentioned issues. The proposed method avoids altogether the use of the error gradient and relies on direct cost function evaluations. A virtualization scheme is used to assess the accuracy improvements when the model is subject to parametric or structural modifications, without directly affecting the control performance. Several simulation examples are discussed to show the effectiveness of the proposed algorithms.     

Sliding window proper orthogonal decomposition: Application to linear and nonlinear modal identification

The Proper Orthogonal Decomposition (POD) method is a tool well adapted to analyze vector signals whereas Continuous Gabor Transform (CGT) is suitable for scalar signal with multi-frequency components. In this paper, a method named Sliding Window Proper Orthogonal Decomposition (SWPOD) combining POD and CGT to analyze Multi-Degrees-Of-Freedom (MDOF) vibration system responses is presented. SWPOD gives access to the evolution of the coherent spacial structures and their frequency components versus time. The method is of principal interest in the case of swept-sine excitation of linear or nonlinear systems to access the resonance frequencies, mode shapes and modal damping ratios. A procedure is proposed to extract the linear and nonlinear normal modes of weakly damped MDOF mechanical systems and illustrated using numerical examples.     

A nonlinear model for calibration of blood glucose noninvasive measurement using near infrared spectroscopy

In order to improve prediction accuracy of calibration in human blood glucose noninvasive measurement using near infrared (NIR) spectroscopy, a modified uninformative variable elimination (mUVE) method combined with kernel partial least squares (KPLS), named as mUVE–KPLS, is proposed as an alternative nonlinear modeling strategy. Under the mUVE method, high-frequency noise and matrix background can be eliminated simultaneously, which provide a optimized data for calibration in sequence; under the kernel trick, a nonlinear relationship of response variable and predictor variables is constructed, which is different with PLS that is a complex model and inappropriate to describe the underlying data structure with significant nonlinear characteristics. Two NIR spectra data of basic research experiments (simulated physiological solution samples experiment in vitro and human noninvasive measurement experiment in vivo) are introduced to evaluate the performance of the proposed method. The results indicate that, after elimination high-frequency noise and matrix background from optical absorption of water in NIR region, a high-quality spectra data is employed in calibration; and under the selection of kernel function and kernel parameter, the best prediction accuracy can be got by KPLS with Gaussian kernel compared with Spline-PLS and PLS. It is encouraging that mUVE–KPLS is a promising nonlinear calibration strategy with higher prediction accuracy for blood glucose noninvasive measurement using NIR spectroscopy.     

不确定单模激光Lorenz系统函数投影同步控制研究

基于Lyapunov稳定性理论,以不确定单模激光Lorenz系统作为驱动系统,不确定Chen系统作为响应系统,利用自适应控制方法,设计了非线性反馈控制器及参数识别器,使响应系统的所有状态变量严格地按函数比例跟踪驱动系统的混沌轨迹,并辨识出包括非线性项在内的驱动系统和响应系统的所有不确定参数。利用四阶龙格-库塔仿真模拟,结果表明了该方法的有效性,设计的函数投影同步控制的方法能更有效地提高保密通信的性能。     

Air pressure broadening and shifting of high-J lines of (00011) ← (00001) band of CO2

The absorption spectra of carbon dioxide (isotope 626, natural abundance in air, ambient temperature) have been studied at total pressures 68-570 Torr with spectral resolution 0.003-0.005 cm⁻¹. The spectra were measured in the spectral domain of 2273-2393 cm⁻¹ by FTIR spectrometer Bruker IFS 125 HR equipped with White-type multipass cell (6.4-41.6 m) and with a cell having 10 cm optical path length. Pressure broadening and shift coefficients were obtained from a series of spectra by means of a nonlinear least-squares spectral fitting technique for the lines of the (00011)←(00001) band with rotational quantum number up to J=82. For fitting of the individual line shapes, we used the Voigt profile with pre-calculated Doppler broadening parameter. The experimental pressure broadening and shift coefficients are compared with the values available in spectroscopic databases HITRAN 2008 and Carbon Dioxide Spectroscopic Databank (CDSD-296) and with other experimental values reported in the literature.     

Time-domain quantification of series of biomedical magnetic resonance spectroscopy signals.

Quantification of individual magnetic resonance spectroscopy (MRS) signals is possible in the time domain using interactive nonlinear least-squares fitting methods which provide maximum likelihood parameter estimates under certain assumptions or using fully automatic, but statistically suboptimal, black-box methods. In kinetic experiments time series of consecutive MRS spectra are measured in which information concerning the time evolution of some of the signal parameters is often present. The purpose of this paper is to show how AMARES, a representative example of the interactive methods, can be extended to the simultaneous processing of all spectra in the time series using the common information present in the spectra. We show that this approach yields statistically better results than processing the individual signals separately.     

Hyperchaos and quasiperiodicity from a four-dimensional system based on the Lorenz system

This paper reports on numerically computed parameter plane plots for a dynamical system modeled by a set of five-parameter, four autonomous first-order nonlinear ordinary differential equations. The dynamical behavior of each point, in each parameter plane, is characterized by Lyapunov exponents spectra. Each of these diagrams indicates parameter values for which hyperchaos, chaos, quasiperiodicity, and periodicity may be found. In fact, each diagram shows delimited regions where each of these behaviors happens. Moreover, it is shown that some of these parameter planes display organized periodic structures embedded in quasiperiodic and chaotic regions.     

Robust analysis of multiplexed SERS microscopy of Ag nanocubes using an alternating minimization algorithm

To drive the application of surface‐enhanced Raman spectroscopy (SERS) mapping in ex vivo diagnostic imaging and non‐biological material characterization, we have designed a robust and accurate multiplex spectral fitting method using an alternating minimization algorithm to extract individual constituent Raman spectra with very small overall fitting error (as low as 2%). For each mixed Raman signal, constituent spectra and mixture coefficients were estimated jointly based on reference spectra that were measured in the lab. Our method is based on a Poisson model to reflect the photon counting nature of Raman signals and includes the nonlinear noise in the measured data, making our method robust against data containing relatively large random noise. In our method, we minimized a cost function consisting of two terms: (1) the overall fitting error between the measured and modeled spectra and (2) the sum of the individual error between each reference spectrum and its corresponding constituent. This method inherently guarantees that the estimates will approach the global minimum with monotonic convergence. The accuracy of our method was validated by applying it to a SERS spectral fitting problem and comparing our results to those from existing methods. Copyright © 2013 John Wiley & Sons, Ltd.     

The NCSTAR model as an alternative to the GWR model

This paper compares the GWR model, usually used to integrate and examine the spatial heterogeneity of a relationship, and the NCSTAR model. The former will give a vector of local parameter estimates for each observation of the data set, according to its nearest neighbors in space. However, it supposes that all variables enter linearly the model. To correct this failure, a NCSTAR model is proposed. It can be seen as a linear model which coefficients are given by the outputs of an ANN model. These outputs can be related not only to geographical variables but also to social, financial or economic variables (according the nature of the relationship under study) via a nonlinear function which functional form has not to be specified. Moreover, the confidence intervals for the NCSTAR estimates can be computed.     

A strategy for multivariate calibration based on modified single-index signal regression: Capturing explicit non-linearity and improving prediction accuracy

In this paper, a modified single-index signal regression (mSISR) method is proposed to construct a nonlinear and practical model with high-accuracy. The mSISR method defines the optimal penalty tuning parameter in P-spline signal regression (PSR) as initial tuning parameter and chooses the number of cycles based on minimizing root mean squared error of cross-validation (RMSECV). mSISR is superior to single-index signal regression (SISR) in terms of accuracy, computation time and convergency. And it can provide the character of the non-linearity between spectra and responses in a more precise manner than SISR. Two spectra data sets from basic research experiments, including plant chlorophyll nondestructive measurement and human blood glucose noninvasive measurement, are employed to illustrate the advantages of mSISR. The results indicate that the mSISR method (i) obtains the smooth and helpful regression coefficient vector, (ii) explicitly exhibits the type and amount of the non-linearity, (iii) can take advantage of nonlinear features of the signals to improve prediction performance and (iv) has distinct adaptability for the complex spectra model by comparing with other calibration methods. It is validated that mSISR is a promising nonlinear modeling strategy for multivariate calibration.     

NIR光谱的LLE-PLS非线性建模方法及应用

传统的偏最小二乘(PLS)建模方法不能有效反映近红外(NIR)光谱与分析样本的物理化学性质之间存在的非线性关系。局部线性嵌入(LLE)是一种新的非线性降维方法,属于流形学习方法,它能有效地发现高维数据中的本真低维结构。结合LLE和PLS,提出一种近红外光谱非线性建模的新方法,并用于建立丹参多酚酸盐柱层析过程中丹酚酸B含量的回归校正模型。该方法首先用LLE对NIR光谱数据降维,再用PLS建立校正模型。结果表明,与多元散射校正、一阶导等预处理方法结合PLS建模比较,参数优化后的LLE-PLS方法能更准确地预测丹酚酸B的含量,其交叉验证均方根误差为0.128 mg·mL-1、决定系数为0.998 8。基于NIR光谱及LLE-PLS建模,可实现丹参多酚酸盐柱层析过程的在线检测。     

Influence of inerter on natural frequencies of vibration systems

This paper investigates the influence of inerter on the natural frequencies of vibration systems. First of all, the natural frequencies of a single-degree-of-freedom (SDOF) system and a two-degree-of-freedom (TDOF) system are derived algebraically and the fact that the inerter can reduce the natural frequencies of these systems is demonstrated. Then, to further investigate the influence of inerter in a general vibration system, a multi-degree-of-freedom system (MDOF) is considered. Sensitivity analysis is performed on the natural frequencies and mode shapes to demonstrate that the natural frequencies of the MDOF system can always be reduced by increasing the inertance of any inerter. The condition for a general MDOF system of which the natural frequencies can be reduced by an inerter is also derived. Finally, the influence of the inerter position on the natural frequencies is investigated and the efficiency of inerter in reducing the largest natural frequencies is verified by simulating a six-degree-of-freedom system, where a reduction of more than 47 percent is obtained by employing only five inerters.     

A Bayesian approach to identifying structural nonlinearity using free-decay response: Application to damage detection in composites

This work discusses a Bayesian approach to approximating the distribution of parameters governing nonlinear structural systems. Specifically, we use a Markov Chain Monte Carlo method for sampling the posterior parameter distributions thus producing both point and interval estimates for parameters. The method is first used to identify both linear and nonlinear parameters in a multiple degree-of-freedom structural systems using free-decay vibrations. The approach is then applied to the problem of identifying the location, size, and depth of delamination in a model composite beam. The influence of additive Gaussian noise on the response data is explored with respect to the quality of the resulting parameter estimates.     

The effect of porosity on the laser induced damage threshold of TiO2 and ZrO2 single layer films

Monolayer ZrO₂ and TiO₂ films were prepared on BK7 glass by physical vapor deposition (PVD) and were subsequently annealed for 1 h at 300 °C. By using the transmission spectra of two samples and the envelope method, the refractive index dispersion and extinction coefficients have been calculated. Laser induced damage threshold (LIDT) measurement shows that despite slight differences between the extinction coefficients of the two samples, the LIDT parameter of the ZrO₂ film is greater than that of the TiO₂ film. This fact leads us to consider thermal conductivity as an important parameter for interpreting the LIDT difference. According to our theoretical analysis, as a consequence of increase in the number of thermal barriers along poorer film, its thermal conductivity, and hence LIDT, decreased, which is in agreement with our experimental results. The measured porosity of the two samples shows higher porosity for TiO₂ single layer, which is in agreement with atomic force (AFM) images. The gradual and smooth damage morphology of ZrO₂ observed in optical images implies higher thermal conductivity than TiO₂.     

A Novel Method for Vibration Mitigation of Complex Mechanical Systems

Taking the complex mechanical systems as the research project, a theoretical multi-degree-of-freedom (MDOF) model was established. Based on the vibration characteristics analysis of this system, a novel method of vibration mitigation was proposed, which can be applied to most of the complex mechanical systems. Through this method, limited grounding stiffness was made use of and added to certain degree of freedom (DOF) discretely. Thus, the root-meansquare (RMS) of the systems amplitude can be reduced to ideal level. The MATLAB code based on this method was attached, which was tested on the theoretical model. Consider that complex mechanical systems are nonlinear and uncertain, theoretically the optimal solution of vibration mitigation is inaccessible. However, this method can always provide a relatively effective solution.     

Interaction of a non-self-adjoint one-dimensional continuum and moving multi-degree-of-freedom oscillator

A method for computing the dynamic responses due to the interaction of two non-self-adjoint systems: a linear, one-dimensional (1D) continuum and a linear, multi-degree-of-freedom (MDOF) oscillator travelling over the continuum, is presented. The solution method is applicable to a broad class of 1D continua, whose dynamics may be governed by various linear operators and subjected to different boundary conditions. The problem is reduced to the integration of a system of linear differential equations with time dependent coefficients. These coefficients are found to depend on eigenvalues as well as eigenfunctions and eigenvectors of the continuum and the oscillator. Two examples are included, representing bridge and railway track vibrations, to demonstrate the application of the method and discuss its convergence.     

拉曼光谱结合PSO-LSSVM算法检测三组分食用调和油含量

提出了一种将拉曼光谱和基于粒子群的最小二乘支持向量机(PSO-LSSVM)算法相结合快速定量检测三组分食用调和油含量的方法。以三组分的食用调和油为研究对象,对拉曼光谱分四步进行了预处理,进而准确提取拉曼光谱的特征峰强度。以训练集样本的特征峰强度和调和油样品的百分比含量作为回归预测模型的输入值和输出值,建立LSSVM和PSO-LSSVM数学模型,通过测试集样本的相关系数和均方误差对模型的预测能力进行分析。非线性建模的最小二乘支持向量机(LSSVM)算法的核函数参数σ和正则化参数γ对模型的学习和泛化能力影响很大,导致模型的预测精度和泛化能力过度依赖于参数--在优化步长过小时耗时较长,过大时又无法得到全局最优值。提出的PSO-LSSVM算法,利用粒子群全局优化能力和收敛速度快的特点对LSSVM的模型参数σ和γ进行优化,从而克服LSSVM算法中耗时与盲目性的问题。分析结果表明,PSO-LSSVM算法对三组分食用调和油中大豆油、花生油和葵花仁油定量预测模型的测试集相关系数分别为0.967 7,0.997 2,0.995 3;均方误差分别为0.054 9,0.009 2,0.047 1。与LSSVM算法相比,PSO-LSSVM模型的预测精度更高。因此,该方法可以快速、准确地检测三组分食用调和油的含量。     

The single basis filter diagonalization method: a rapid multidimensional data processing scheme

A new way to apply the filter diagonalization method (FDM) that results in a large increase in the speed of calculation of multidimensional NMR spectra is presented. The speed increase is accompanied by slight differences in spectral lineshapes, although frequency estimates remain essentially identical. For contoured spectra, the method does not result in appreciable differences from the full FDM calculation. Optimal parameter sets for an FDM calculation can be estimated far more rapidly, which makes the FDM more straightforward to employ in practice. The performance of the method versus the full FDM was investigated for both model and experimental signals. The effect of noise on the method was also studied.     

重金属铅离子胁迫下玉米叶片光谱弱差信息的DSAT甄别模型

光谱间微弱信息测度是当今高光谱遥感研究难点之一,传统光谱测度方法难以区分光谱信息的微弱差异。研究设计了不同浓度的铅(Pb)污染实验,并测量了不同浓度铅离子(Pb2+)胁迫下玉米叶片的高光谱反射率、叶绿素含量及Pb2+含量,但是从所测结果得出,不同浓度Pb2+胁迫下的光谱相似性相关系数均达到0.999,难以区分不同浓度Pb2+胁迫引发的光谱间微弱信息差异和污染程度。针对这一情况,基于光谱微分处理、正切函数增强、光谱角量度与波谱分段检测等,提出了一种新型的相似光谱测度方法,即微分光谱角正切(derivative spectral angle tangent,DSAT)法。为了验证DSAT在区分相关系数达0.99以上相似光谱的可行性和有效性,将DSAT用于不同浓度Pb2+胁迫玉米叶片的整体波形与光谱区间子波形的信息差异性度量与检测。实验结果得到,波形差异信息与玉米叶片中叶绿素相对浓度与Pb2+含量显著相关。进而也证明DSAT法在甄别较高相似性光谱间差异上具有更好的实用性和优越性。     

多重结构的体全息存储傅里叶变换光学系统设计

分析了体全息存储傅里叶变换光学系统的设计要求和光学参量的确定。采用多重结构方法对傅里叶变换镜头的正向和逆向光路同时进行了优化,可实现对两对物像共扼位置控制像差。给出了前后组焦距分别为44mm和40mm的达到衍射受限要求的4片型球面全息存储光学系统的设计结果。