Using Wavelets for the Detection of Discrete Events in Time Series of Hybrid Systems

This contribution deals with the use of wavelets for the analysis of time series of systems which are hybrid in the sense that they contain discrete and continuous dynamics. We focus on the detection of discrete events which is an important step in the identification of hybrid systems. A brief overview of the characteristics of the wavelet transform is given, which shows that the wavelet transform is an appropriate method for the analysis of time series of hybrid systems. By the combination of two wavelet-based analysis techniques, a two-step procedure is obtained which allows the detection of switching points in the presence of weak noise. In this context, emphasis is given to the problems which arise when the theoretical results are used to detect discrete events in real time series. The procedure is demonstrated for a time series obtained from the simulation of a nonlinear laboratory plant.     

小波包变换及代价函数设计综述

小波包是小波理论的重要组成部分,在非平稳信号特征检测和故障诊断中具有广泛的应用。小波包教学是小波分析教学的一个难点,也是一个较容易忽视的知识点。本文分析了小波包理论,归纳总结了小波包目标函数,以及它们适用的领域,并提出了新的目标函数。本文可以对小波包的教学提供一些新的思路。     

基于小波分析理论的复杂岩性区块油水层识别方法

基于伊通盆地双二段储层岩性变化快,沉积模式复杂等特点,利用小波变换对测井信号进行去高频噪音处理,再运用多分辨率分析、小波包分析对该研究区目的层段流体进行识别.结果表明:去噪处理后的信号在保持原有信号特性的基础上,将高频噪音产生的影响去除,具有高保真,高信噪比的优点.运用小波分析理论,结合分频能量叠加原理对储层流体进行识别,解释正确率在80%以上,远优于常规解释方法,有效地解决了在复杂岩性区块油水层识别难度大的问题.     

Dynamical behaviour and exact solutions of thirteenth order derivative nonlinear Schr\"{o}dinger equation

In this paper, we considered the model of the thirteenth order derivatives of nonlinear Schr\"{o}dinger equations. It is shown that a wave packet ansatz inserted into these equations leads to an integrable Hamiltonian dynamical sub-system. By using bifurcation theory of planar dynamical systems, in different parametric regions, we determined the phase portraits. In each of these parametric regions we obtain possible exact explicit parametric representation of the traveling wave solutions corresponding to homoclinic, hetroclinic and periodic orbits.     

一类四元数小波包的构造

实值二维信号可以用四元数来表示,因此,四元数的尺度函数和小波的构造就成为分析二维信号的关键．引入了四元数小波包的概念,并且借助于四元数多分辨分析和四元数尺度函数和四元数小波函数的概念和若干公式,给出并构造了一类四元数正交小波包的构造方法,得到了四元数正交小波包的3个正交性公式,最后,利用四元数正交小波包给出了L^2（R...     

Parameterization and algebraic structure of 3-band orthogonal wavelet systems

In this paper, a complete parameterization for the 3-band compact wavelet systems is presented. Using the parametric result, a program of the filterbank design is completed, which can give not only the filterbanks but also the graphs of all possible scaling functions and their corresponding wavelets. Especially some symmetric wavelets with small supports are given. Finally an algebraic structure for this kind of wavelet systems is characterized.     

Explicit constructions and properties of generalized shift-invariant systems in $L^{2}(\mathbb {R})$

Generalized shift-invariant (GSI) systems, originally introduced by Hernández et al. and Ron and Shen, provide a common frame work for analysis of Gabor systems, wavelet systems, wave packet systems, and other types of structured function systems. In this paper we analyze three important aspects of such systems. First, in contrast to the known cases of Gabor frames and wavelet frames, we show that for a GSI system forming a frame, the Calderón sum is not necessarily bounded by the lower frame bound. We identify a technical condition implying that the Calderón sum is bounded by the lower frame bound and show that under a weak assumption the condition is equivalent with the local integrability condition introduced by Hernández et al. Second, we provide explicit and general constructions of frames and dual pairs of frames having the GSI-structure. In particular, the setup applies to wave packet systems and in contrast to the constructions in the literature, these constructions are not based on characteristic functions in the Fourier domain. Third, our results provide insight into the local integrability condition (LIC).     

Generalized Derivatives for Solutions of Parametric Ordinary Differential Equations with Non-differentiable Right-Hand Sides

Sensitivity analysis provides useful information for equation-solving, optimization, and post-optimality analysis. However, obtaining useful sensitivity information for systems with nonsmooth dynamic systems embedded is a challenging task. In this article, for any locally Lipschitz continuous mapping between finite-dimensional Euclidean spaces, Nesterov’s lexicographic derivatives are shown to be elements of the plenary hull of the (Clarke) generalized Jacobian whenever they exist. It is argued that in applications, and in several established results in nonsmooth analysis, elements of the plenary hull of the generalized Jacobian of a locally Lipschitz continuous function are no less useful than elements of the generalized Jacobian itself. Directional derivatives and lexicographic derivatives of solutions of parametric ordinary differential equation (ODE) systems are expressed as the unique solutions of corresponding ODE systems, under Carathéodory-style assumptions. Hence, the scope of numerical methods for nonsmooth equation-solving and local optimization is extended to systems with nonsmooth parametric ODEs embedded.     

Estimating copula densities through wavelets

Wavelet analysis is used to construct a rank-based estimator of a copula density. The procedure, which can be easily implemented with ready-to-use wavelet packages, is based on an algorithm that handles boundary effects automatically. The resulting estimator provides a non-parametric benchmark for the selection of a parametric copula family. From a theoretical point of view, the estimation procedure is shown to be optimal in the minimax sense on a large functional class of regular copula densities. The approach is illustrated with actuarial and financial data.     

基于非线性混沌时序动力系统的预测方法研究

主要研究由混沌时序所确定的非线性动力系统的预测方法．研究了非线性自相关混沌模型的结构,模型阶数的确立技术．将神经网络和小波理论相结合,研究了小波变换神经网络的结构,给出了小波神经网络的学习方法;提出了一种新的基于小波网络的参数辨识方法．该方法可以有选择地提取时序中的不同的时间、频率尺度,实现原时序的趋势或细节预测．通过对混沌时序进行预处理,并比较预处理后的预测结果,得到了一些有益的结果:用非线性自相关混沌模型采用小波网络对模型参数进行辨识,其辨识的准确程度较高,用该模型对混沌时序(包括含有噪声)的预测比较有效．     

Composite wavelet bases for operator equations

This paper is concerned with the construction of biorthogonal wavelet bases defined on a union of parametric images of the unit -cube. These bases are to satisfy certain requirements imposed by applications to a class of operator equations acting on such domains. This covers also elliptic boundary value problems, although this study is primarily motivated by our previous analysis of wavelet methods for pseudo-differential equations with special emphasis on boundary integral equations. In this case it is natural to model the boundary surface as a union of parametric images of the unit cube. It will be shown how to construct wavelet bases on the surface which are composed of wavelet bases defined on each surface patch. Here the relevant properties are the validity of norm equivalences in certain ranges of Sobolev scales, as well as appropriate moment conditions.

     

一种半正交小波包——B__小波包理论、算法及实现

信号的正交小波包表示具有数学上的简捷性和优美性 ,然而已经证明 ,除去 Haar小波包外 ,全体紧支撑正交小波包生成元不具有广义线性相位 ,因而重构的信号将不可避免地产生失真。本文提出并证明了一种半正交小波包—— B 小波包 ,它具有广义线性相位 ,因而可以不失真地回复原始信号 ,这一点在工程应用中是非常重要的 ,本文的算例也显示了其优越性     

Hierarchical multi-objective decision systems for general resource allocation problems

We consider optimization methods for hierarchical power-decentralized systems composed of a coordinating central system and plural semi-autonomous local systems in the lower level, each of which possesses a decision making unit. Such a decentralized system where both central and local systems possess their own objective function and decision variables is a multi-objective system. The central system allocates resources so as to optimize its own objective, while the local systems optimize their own objectives using the given resources. The lower level composes a multi-objective programming problem, where local decision makers minimize a vector objective function in cooperation. Thus, the lower level generates a set of noninferior solutions, parametric with respect to the given resources. The central decision maker, then, parametric with respect to the given resources. The central decision maker, then, chooses an optimal resource allocation and the best corresponding noninferior solution from among a set of resource-parametric noninferior solutions. A computational method is obtained based on parametric nonlinear mathematical programming using directional derivatives. This paper is concerned with a combined theory for the multi-objective decision problem and the general resource allocation problem.The authors are indebted to Professor G. Leitmann for his valuable comments and suggestions.     

Sensitivity analysis of discontinuous parametric periodic systems

The paper concerns the complex eigensolutions sensitivity analysis of parametric periodic system. The derivatives of (so called) monodromy matrix (Floquet transient matrix) were the first calculated. Then the first derivatives of multiplicators, which are the complex eigenvalues of monodromy matrix, were obtained. The theory has been expanded to cover a class of discontinuous parametric periodic excitation. Furthermore, the method was generalized, so that the system parameters, on which the parametric excitation period depends, can now be a design parameter. In particular, it has become possible to use the parametric excitation period as a design parameter. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Noiselets

Noiselets are functions which are noise-like in the sense that they are totally uncompressible by orthogonal wavelet packet methods. We describe a library of such functions and demonstrate a few of their noise-like properties.     

Generalized sensitivity analysis of nonlinear programs using a sequence of quadratic programs

ABSTRACT

Local sensitivity information is obtained for KKT points of parametric NLPs that may exhibit active set changes under parametric perturbations; under appropriate regularity conditions, computationally relevant generalized derivatives of primal and dual variable solutions of parametric NLPs are calculated. Ralph and Dempe obtained directional derivatives of solutions of parametric NLPs exhibiting active set changes from the unique solution of an auxiliary quadratic program. This article uses lexicographic directional derivatives, a newly developed tool in nonsmooth analysis, to generalize the classical NLP sensitivity analysis theory of Ralph and Dempe. By viewing said auxiliary quadratic program as a parametric NLP, the results of Ralph and Dempe are applied to furnish a sequence of coupled QPs, whose unique solutions yield generalized derivative information for the NLP. A practically implementable algorithm is provided. The theory developed here is motivated by widespread applications of nonlinear programming sensitivity analysis, such as in dynamic control and optimization problems.     

Computation of eigenpair partial derivatives by Rayleigh–Ritz procedure

Based on Rayleigh–Ritz procedure, a new method is proposed for a few eigenpair partial derivatives of large matrices. This method simultaneously computes the approximate eigenpairs and their partial derivatives. The linear systems of equations that are solved for eigenvector partial derivatives are greatly reduced from the original matrix size. And the left eigenvectors are not required. Moreover, errors of the computed eigenpairs and their partial derivatives are investigated. Hausdorff distance and containment gap are used to measure the accuracy of approximate eigenpair partial derivatives. Error bounds on the computed eigenpairs and their partial derivatives are derived. Finally numerical experiments are reported to show the efficiency of the proposed method.     

向量值正交小波包

引进对应于2尺度向量值尺度函数的多分辨分析和向量值小波的概念.给出向量值小波包的定义及其构造算法,研究了向量值正交小波包的正交性,并讨论了空间L2(R,CN)的正交分解.     

Parametric solution to the joint system identification and optimization problem

This study is concerned with the simultaneous identification and optimization of static systems. The necessity and the advantages of an integrated approach to the identification and optimization of the system model is established theoretically as well as computationally. A parametric approach to the integrated problem is proven to converge to the integrated problem solution. The general methodology of decomposition of large-scale systems is extended by implementingfeasible decomposition of the joint problem. A multilevel approach is then utilized to successfully solve example problems. Handling the system constraints via a penalty-function technique is shown to be an efficient approach when using the parametric formulation of the joint problem. Numerical results for two example problems are presented using the Univac 1108 digital computer, revealing the economic advantages and disadvantages of the integrated approach to the identification and optimization problems.The authors wish to thank Messieurs I. Lefkowitz, L. S. Lasdon, F. Gembicki, and O. B. Olagundoye for their critique, comments, and suggestions during the course of this study.     

Statistical Analysis of Financial Volatility by Wavelet Shrinkage

We analyze the Nikkei daily stock index and verify how wavelets can help in identifying, estimating and predicting its volatility features. While we study the conditional mean and variance dynamics, by utilizing statistical parametric inference techniques, we also decompose the observed signal with a data de-noising procedure. We thus investigate how wavelets discriminate among information at different resolution levels and we attempt to understand whether the de-noised data lead to a better identification of the underlying volatility process. We find that the wavelet data pre-processing strategy, by reducing the measurement error of the observed data, is useful for improving the volatility prediction power.