Nonlinear wavelet estimation of regression function with random desigm

The nonlinear wavelet estimator of regression function with random design is constructed. The optimal uniform convergence rate of the estimator in a ball of Besov spaceB 3 p,q is proved under quite general assumpations. The adaptive nonlinear wavelet estimator with near-optimal convergence rate in a wide range of smoothness function classes is also constructed. The properties of the nonlinear wavelet estimator given for random design regression and only with bounded third order moment of the error can be compared with those of nonlinear wavelet estimator given in literature for equal-spaced fixed design regression with i.i.d. Gauss error.

Nonlinear Wavelet Methods for High-dimensional Backward Heat Equation

The backward heat equation is a typical ill-posed problem. In this paper, we shall apply a dual least squares method connecting Shannon wavelet to the following equation Motivated by Reginska＇s work, we shall give two nonlinear approximate methods to regularize the approximate solutions for high-dimensional backward heat equation, and prove that our methods are convergent.

JUMP DETECTION BY WAVELET IN NONLINEAR AUTOREGRESSIVE MODELS

Wavelets are applied to detection of the jump points of a regression function in nonlinear autoregressive model x(t) = T(x(t-1)) + epsilon t. By checking the empirical wavelet coefficients of the data,which have significantly large absolute values across fine scale levels, the number of the jump points and locations where the jumps occur are estimated. The jump heights are also estimated. All estimators are shown to be consistent. Wavelet method ia also applied to the threshold AR(1) model(TAR(1)). The simple estimators of the thresholds are given,which are shown to be consistent.

Nonlinear Adaptive Wavelet Transform for Lossless Image Compression

The paper presents a class of nonlinear adaptive wavelet transforms for lossless image compression. In update step of the lifting the different operators are chosen by the local gradient of original image. A nonlinear morphological predictor follows the update adaptive lifting to result in fewer large wavelet coefficients near edges for reducing coding. The nonlinear adaptive wavelet transforms can also allow perfect reconstruction without any overhead cost. Experiment results are given to show lower entropy of the adaptive transformed images than those of the non-adaptive case and great applicable potentiality in lossless image compresslon.

A high-order accurate wavelet method for solving Schrdinger equations with general nonlinearity

A sampling approximation for a function defined on a bounded interval is proposed by combining the Coiflet-type wavelet expansion and the boundary extension technique. Based on such a wavelet approximation scheme, a Galerkin procedure is developed for the spatial discretization of the generalized nonlinear Schr6dinger （NLS） equa- tions, and a system of ordinary differential equations for the time dependent unknowns is obtained. Then, the classical fourth-order explicit Runge-Kutta method is used to solve this semi-discretization system. To justify the present method, several widely considered problems are solved as the test examples, and the results demonstrate that the proposed wavelet algorithm has much better accuracy and a faster convergence rate in space than many existing numerical methods.

Analysis of a Gyroscope′s Rotor Nonlinear Supported Magnetic Field Based on the B-Spline Wavelet-FEM

A supported framework of a gyroscope＇s rotor is designed and the B-Spline wavelet finite element model of nonlinear supported magnetic field is worked out. A new finite element space is studied in which the scaling function of the B-spline wavelet is considered as the shape function of a tetrahedton. The magnetic field is spited by an artificial absorbing body which used the condition of field radiating, so the solution is unique. The resolution is improved via the varying gradient of the B-spline function under the condition of unchanging gridding. So there are some advantages in dealing with the focus flux and a high varying gradient result from a nonlinear magnetic field. The result is more practical. Plots of flux and in the space is studied via simulating the supported system model. The results of the study are useful in the research of the supported magnetic system for the gyroscope rotor.

WAVELET-BASED ESTIMATORS OF MEAN REGRESSION FUNCTION WITH LONG MEMORY DATA

This paper provides an asymptotic expansion for the mean integrated squared error （MISE） of nonlinear wavelet-based mean regression function estimators with long memory data. This MISE expansion, when the underlying mean regression function is only piecewise smooth, is the same as analogous expansion for the kernel estimators.However, for the kernel estimators, this MISE expansion generally fails if the additional smoothness assumption is absent.

Nonlinear approximation of image based on monoscale orthonormal ridgelets frame

A new tight frame called as monoscale orthonormal ridgelet frame （MORF） is proposed. The localization principle and the orthonormal ridgelet constructed by Donoho are applied to construct the MORF, which are used to evaluate the order of nonlinear approximation for image with edge. Because the new tight frame not only has directionality but also bears orthonormality. It overcomes redundancy of Candes＇s monoscale ridgelets and provides many excellent properties in practical application. Theoretical analysis and experiments demonstrate that the new frame has remarkable potential for image compression, image reconstruction, and image denoising with the simple refinement for MORF.

Wavelet method applied to specific adhesion of elastic solids via molecular bonds

We propose a wavelet method to analyze the stochastic-elastic problem of specific adhesion between two elastic solids via ligand-receptor bond clusters, which is governed by a nonlinear integro-differential equation with a sin- gular Cauchy kernel to describe the mean-field coupling between deformation of elastic materials and stochastic behavior of the molecular bonds. To solve this problem, Galerkin method based on a wavelet approximation scheme is adopted, and special treatment which transforms the singular Cauchy kernel into a smooth one has been proposed to avoid the cumbersome calculation of singular integrals. Numerical results demonstrate that the method is fully capable of solving the specific adhesion problems with complex nonlinear and singular equations. Based on the proposed method, investigations are performed to reveal the relation between steady-state pulling force and mean surface separation under different stress concentration indexes, which is crucial for assembling the overall constitutive relations for multicellular tumor spheroids and polymer-matrix microcomposites.

Laboratory Study of the Nonlinear Transformation of Irregular Waves over A Mild Slope

This paper considers the nonlinear transformation of irregular waves propagating over a mild slope （1：40）. Two cases of irregular waves, which are mechanically generated based on JONSWAP spectra, are used for this purpose. The results indicate that the wave heights obey the Rayleigh distribution at the offshore location; however, in the shoaling region, the heights of the largest waves are underestimated by the theoretical distributions. In the surf zone, the wave heights can be approximated by the composite Weibull distribution. In addition, the nonlinear phase coupling within the irregular waves is investigated by the wavelet-based bicoherence. The bicoherence spectra reflect that the number of frequency modes participating in the phase coupling increases with the decreasing water depth, as does the degree of phase coupling. After the incipient breaking, even though the degree of phase coupling decreases, a great number of higher harmonic wave modes are also involved in nonlinear interactions. Moreover, the summed bicoherence indicates that the frequency mode related to the strongest local nonlinear interactions shifts to higher harmonics with the decreasing water depth.

APPLICATION OF WAVELET TRANSFORM TO BIFURCATION AND CHAOS STUDY

The response of a nonlinear vibration system may be of three types, namely, periodic, quasiperiodic or chaotic,,when the parameters of the system are changed. The periodic motions can be identified by Poincare map, and harmonic wavelet transform (HWT) can distinguish quasiperiod from chaos, so the existing domains of different types of motions of the system can be revealed in the parametric space with the method of HWT joining with Poincare map.

An optimal adaptive H-infinity tracking control design via wavelet network

In this paper, an optimal adaptive H-infinity tracking control design method via wavelet network for a class of uncertain nonlinear systems with external disturbances is proposed to achieve H-infinity tracking performance. First, an alternate tracking error and a performance index with respect to the tracking error and the control effort are introduced in order to obtain better performance, especially, in reducing the cost of the control effort in the case of small attenuation levels. Next, H-infinity tracking performance, which attenuates the influence of both wavelet network approximation error and external disturbances on the modified tracking error, is formulated. Our results indicate that a small attenuation level does not lead to a large control signal. The proposed method insures an optimal trade-off between the amplitude of control signals and the performance of tracking errors. An example is given to illustrate the design efficiency.

The Adaptive Wavelet Collocation Method and Its Application in Front Simulation

The adaptive wavelet collocation method （AWCM） is a variable grid technology for solving partial differential equations （PDEs） with high singularities. Based on interpolating wavelets, the AWCM adapts the grid so that a higher resolution is automatically attributed to domain regions with high singularities. Accuracy problems with the AWCM have been reported in the literature, and in this paper problems of efficiency with the AWCM are discussed in detail through a simple one-dimensional （1D） nonlinear advection equation whose analytic solution is easily obtained. A simple and efficient implementation of the AWCM is investigated. Through studying the maximum errors at the moment of frontogenesis of the 1D nonlinear advection equation with different initial values and a comparison with the finite difference method （FDM） on a uniform grid, the AWCM shows good potential for modeling the front efficiently. The AWCM is also applied to a two-dimensional （2D） unbalanced frontogenesis model in its first attempt at numerical simulation of a meteorological front. Some important characteristics about the model are revealed by the new scheme.

飞行器轨迹的半参数估计方法

提出一种基于半参数建模的飞行器轨迹估计新方法,通过抑制不可参数建模的测量系统误差提高轨迹的估计精度。利用不等距节点B样条函数建立飞行器轨迹的参数模型,将轨迹参数模型代入测量模型中,并将测量模型中不可参数建模的系统误差表示为非参数,进而建立包含轨迹参数待估量和系统误差非参数待估量的半参数回归模型。采用轨迹参数估计和系统误差分离交替迭代的方式求解该半参数回归模型,利用非线性最小二乘法估计轨迹参数,通过小波分析从残差数据中分离系统误差。理论分析和仿真结果表明,半参数估计方法的轨迹估计精度优于忽略测量系统误差的参数估计方法。

Discussion of stability in a class of models on recurrent wavelet neural networks

Based on wavelet neural networks （WNNs） and recurrent neural networks （RNNs）, a class of models on recurrent wavelet neural networks （RWNNs） is proposed. The new networks possess the advantages of WNNs and RNNs. In this paper, asymptotic stability of RWNNs is researched.according to the Lyapunov theorem, and some theorems and formulae are given. The simulation results show the excellent performance of the networks in nonlinear dynamic system recognition.

The Multi-scale Method for Solving Nonlinear Time Space Fractional Partial Differential Equations

In this paper, we present a new algorithm to solve a kind of nonlinear time space-fractional partial differential equations on a finite domain. The method is based on B-spline wavelets approximations, some of these functions are reshaped to satisfy on boundary conditions exactly. The Adams fractional method is used to reduce the problem to a system of equations. By multiscale method this system is divided into some smaller systems which have less computations. We get an approximated solution which is more accurate on some subdomains by combining the solutions of these systems. Illustrative examples are included to demonstrate the validity and applicability of our proposed technique, also the stability of the method is discussed.

NONLINEAR APPROXIMATION WITH GENERAL WAVE PACKETS

We study nonlinear approximation in the Triebel-Lizorkin spaces with dictionaries formed by dilating and translating one single function g. A general Jackson inequality is derived for best m-term approximation with such dictionaries. In some special cases where g has a special structure, a complete characterization of the approximation spaces is derived.

基于相关互补非线性特征融合的嗓音疾病分类

针对单一特征对嗓音疾病分类识别效果不佳和特征组合随机性的问题,文中提出相关互补原则组合非线性特征方法,有效提高了嗓音疾病的分类识别率。应用小波包分解对嗓音疾病信号进行非线性特征提取及主成分分析,对所提取的特征进行分层降维组合,使用SVM分类器对嗓音疾病进行分类识别。实验结果表明,分层降维特征按相关互补原则组合相较于原始特征随机组合在相同的分类器下的准确率提高了6.16%,极大地提高了嗓音疾病的识别率。

基于小波时频分析的疲劳损伤定量表征

许多机械部件中的圆管结构长期在交变应力的工况下服役,容易出现疲劳裂纹,最终导致材料失效酿成事故。非线性超声能够表征疲劳裂纹的损伤程度,而表征损伤程度的非线性系数的提取方法尤为重要。提出一种基于小波变换的时频信号处理方法用以提取疲劳裂纹产生的非线性信号并以此计算非线性系数。首先,分析了多种小波基进行小波变换处理后得到的非线性系数间的量化关系;其次,利用仿真得到带有疲劳裂纹的圆管中的非线性超声导波信号,比较各类非线性系数提取方法得到的不同频率分量幅值随时间变化的信息;最后,建立疲劳裂纹损伤程度与各类方法得到的非线性系数间的量化关系。试验结果表明,所提方法得到的非线性系数能够更好地表征疲劳裂纹的损伤程度。

基于非线性状态估计(NSET)方法的燃机电厂故障检测研究及应用

随着“双碳”目标的提出,燃气轮机发电机组的经济、可靠运行成为了行业关注的重点。因此,准确检测故障和提高运行水平具有重要的研究价值。本文针对燃机电厂的故障检测问题,结合小波去噪等数据预处理方法,提出了一种基于非线性状态估计(NSET)的故障检测方法。该方法利用电力大数据,首先构建记忆矩阵并建立数学模型,然后通过比较实际曲线与预测曲线,分析残差值,从而有效地检测出故障。为了验证其有效性,本文以浙江某燃机电厂为例,在仿真平台和生产现场分别进行实验。实验结果表明,该方法能够有效检测33种故障也能够检测生产现场的燃机速比阀故障、热电偶故障等常见故障。最后,本文将该方法落地到模拟数字电厂项目中,实现了数字电厂故障检测技术的工程示范应用。