Non linear filtering and stochastic textures

In image synthesis the notion of texture plays a fundamental role. Texture can be defined informally on several unit patterns (primitives) scrambled over a given image according to different placement rules. Texture analysis is usually performed using a structural or a statistical approach. The structural approach assumes that a set of primitive unit patterns can be easily identified : it defines the texture as a combination of such primitives. This approach of synthesizing a texture could be used once primitives are known. The statistical approach derives a set of local measurements for a given image over the space domain or the corresponding frequency domain. Features based on these measurements are then used for discrimination between different textures. Several methods have been developped, the main ones are : Fourier analysis, grey-level run length method, second order or first order statistics etc… We will restrict ourselves to the discussion of the probabilistic approach : this method avoids the difficult problem of the boundaries identification. A texture is considered as the realization of a stochastic process X. Now the problem is to find the nature of the process X which we have to use in order to be able to reproduce a picture (ex: grass, bank of trees etc…). A linear filter whose input is a white noise is always used. In this paper we develop a non linear filtering method : the input of the filter is a multidimensional white noise whose components are not necessarily independent and the output process X is an iterated stochastic integral. Several images of textures obtained by such methods are on the end of this article.     

小波基的选取对图像去噪的影响

小波图像去噪方法是现代图像处理中的重要组成部分，小波基的不同选取直接影响到去噪的效果．本文在全局阈值的标准下，通过对噪声水平和图像纹理特征的估计，讨论了小波基的正交性和线性相位性对去噪结果的不同影响，提出了选取小波基的近似标准．     

Static Hedging with Uncertain Quantity and Departure from the Cost-of-Carry Valuation

In this paper, we are concerned with the optimal hedge ratio under quantity risk as well as discrepancies between the futures market price and its theoretical valuation according to the cost- of-carry model. Assuming a geometric Brownian motion for forecasting process, we model mispricing as a specific noise corn poncnt in the dynamics of filturcs market prices, based on which the optimal hedging strategy is calculated. Finally, we illustrate optimal strategy and its properties by numerical examples.     

Robust sparse phase retrieval made easy

In this short note we propose a simple two-stage sparse phase retrieval strategy that uses a near-optimal number of measurements, and is both computationally efficient and robust to measurement noise. In addition, the proposed strategy is fairly general, allowing for a large number of new measurement constructions and recovery algorithms to be designed with minimal effort.     

The tug-of-war without noise and the infinity Laplacian in a wedge

Consider the ending time of the tug-of-war without noise in a wedge. There is a critical angle for finiteness of its expectation when player I maximizes the distance to the boundary and player II minimizes the distance. There is also a critical angle such that for smaller angles, player II can find a strategy where the expected ending time is finite, regardless of player I’s strategy. For larger angles, for each strategy of player II, player I can find a strategy making the expected ending time infinite. Using connections with the inhomogeneous infinity Laplacian, we bound this critical angle.     

A new method for numerical differentiation based on direct and inverse problems of partial differential equations

In this paper, we mainly study a numerical differentiation problem which aims to approximate the second order derivative of a single variable function from its noise data. By transforming the problem into a combination of direct and inverse problems of partial differential equations (heat conduction equations), a new method that we call the PDEs-based numerical differentiation method is proposed. By means of the finite element method and the Tikhonov regularization, implementations of the proposed PDEs-based method are presented with a posterior strategy for choosing regularization parameters. Numerical results show that the PDEs-based numerical differentiation method is highly feasible and stable with respect to data noise.     

Efficient transient noise analysis in circuit simulation

Stochastic differential algebraic equations (SDAEs) arise as a mathematical model for electrical network equations that are influenced by additional sources of Gaussian white noise. We discuss adaptive linear multi-step methods for their numerical integration, in particular stochastic analogues of the trapezoidal rule and the two-step backward differentiation formula, and we obtain conditions that ensure mean-square convergence of this methods. For the case of small noise we present a strategy for controlling the step-size in the numerical integration. It is based on estimating the mean-square local errors and leads to step-size sequences that are identical for all computed paths. Test results illustrate the performance of the presented methods. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

The practical use of noise to improve speech coding by analogue cochlear implants

The addition of noise to speech signals coded by an analogue multichannel cochlear implant has previously been shown in modelling studies to enhance the representation of speech cues by the fine time structure of evoked nerve discharges. The enhancement, however, occurred only for a range of noise levels, and this range was stimulus dependent. Theoretically, fine optimization of the noise levels would be unnecessary if each implant channel stimulated a group of cochlear nerve fibres such that each fibre in the group received an independent noise waveform in addition to the same information-bearing signal. We present results from computer simulations that suggest that current spread in the cochlea may be exploited to obtain a high degree of independence between the noise waveforms that stimulate adjacent fibres. The model simulated monopolar stimulation of a cochlear nerve by 11, 21 or 41 electrodes in the scala tympani. The correlation between the effective stimuli for pairs of nerve fibres and the correlation between the corresponding evoked discharges were calculated for two noise strategies. In one strategy, an independent noise current was applied to each electrode. Less correlation between effective stimuli was obtained with the alternate strategy that used inhibition between the noise sources.     

基于分数阶微积分正则化的图像处理

全变分正则化方法已被广泛地应用于图像处理,利用此方法可以较好地去除噪声,并保持图像的边缘特征,但得到的优化解会产生"阶梯"效应.为了克服这一缺点,本文通过分数阶微积分正则化方法,建立了一个新的图像处理模型.为了克服此模型中非光滑项对求解带来的困难,本文研究了基于不动点方程的迫近梯度算法.最后,本文利用提出的模型与算法进行了图像去噪、图像去模糊与图像超分辨率实验,实验结果表明分数阶微积分正则化方法能较好的保留图像纹理等细节信息.     

Stochastic oscillations in circuit simulation

We consider the simulation of noisy electronic circuits with oscillatory solutions. For their transient noise simulation we use variable step-size two-step schemes for stochastic differential-algebraic equations. The performance of these methods in combination with a suitable step-size control strategy is illustrated by an industrial test application. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

证券投资者的进化博弈模型建立及渐进均衡研究

运用进化博弈相关理论,以我国证券市场中的理性和非理性投资者为局中人建立进化博弈单群体模型,并求解此单群体模型的渐进稳定均衡策略,得到理性与非理性投资者的渐进稳定均衡比例,得出理性交易策略与噪声交易策略应同时存在而且适度的噪声有利于保持市场的流动性的结论,为我国证券市场和政府监管者提出政策性建议.     

Optimal reinsurance-investment strategy for a dynamic contagion claim model

We study the optimal reinsurance-investment problem for the compound dynamic contagion process introduced by Dassios and Zhao (2011). This model allows for self-exciting and externally-exciting clustering effect for the claim arrivals, and includes the well-known Cox process with shot noise intensity and the Hawkes process as special cases. For tractability, we assume that the insurer’s risk preference is the time-consistent mean–variance criterion. By utilizing the dynamic programming and extended HJB equation approach, a closed-form expression is obtained for the equilibrium reinsurance-investment strategy. An excess-of-loss reinsurance type is shown to be optimal even in the presence of self-exciting and externally-exciting contagion claims, and the strategy depends on both the claim size and claim arrivals assumptions. Further, we show that the self-exciting effect is of a more dangerous nature than the externally-exciting effect as the former requires more risk management controls than the latter. In addition, we find that the reinsurance strategy does not always become more conservative (i.e., transferring more risk to the reinsurer) when the claim arrivals are contagious. Indeed, the insurer can be better off retaining more risk if the claim severity is relatively light-tailed.     

Direct Estimation of Linear Functionals from Indirect Noisy Observations

The authors study the efficiency of the linear-functional strategy, as introduced by Anderssen in 1986, for inverse problems with observations blurred by Gaussian white noise with known intensity δ. The optimal accuracy is presented and it is shown how this can be achieved by a linear-functional strategy based on the noisy observations. This optimal linear-functional strategy is obtained from Tikhonov regularization of some dual problem. Next, the situation is treated when only a finite number of noisy observations, given beforehand, is available. Under appropriate smoothness assumptions best possible accuracy still can be attained if the number of observations corresponds to the noise intensity in a proper way. It is also shown that, at least asymptotically, this number of observations cannot be reduced.     

Control costs and potential functions for spatial games

Van Damme and Weibull (1998, 2002) model the noise in games as endogenously determined tremble probabilities, by assuming that with some effort players can control the probability of implementing the intended strategy. Following their methodology, we derive logit-like adjustment rules for games played on quasi-symmetric weighted graphs and explore the properties of the ensuing Markov chain. Received: November 2000/Revised: June 2002     

基于方向多尺度变换和统计建模的纹理分类方法

纹理是图像分析和识别中经常使用的关键特征, 而小波变换则是图像纹理表示和分类中的常用工具. 然而, 基于小波变换的纹理分类方法常常忽略了小波低频子带信息, 并且无法提取图像纹理的块状奇异信息. 本文提出小波子带系数的局部能量直方图建模方法、轮廓波特征的Poisson 混合模型建模方法和基于轮廓波子带系数聚类的特征提取方法, 并将其应用于图像纹理分类上. 基于局部能量直方图的纹理分类方法解决了小波低频子带的建模难题, 基于Poisson 混合模型的纹理分类方法则首次将Poisson 混合模型用于轮廓子带特征的建模, 而基于轮廓波域聚类的纹理分类方法是一种快速的分类方法. 实验结果显示, 本文所提出的三类方法都超过了当前典型的纹理分类方法.     

The Lagrange method for the regularization of discrete ill-posed problems

In many science and engineering applications, the discretization of linear ill-posed problems gives rise to large ill-conditioned linear systems with the right-hand side degraded by noise. The solution of such linear systems requires the solution of minimization problems with one quadratic constraint, depending on an estimate of the variance of the noise. This strategy is known as regularization. In this work, we propose a modification of the Lagrange method for the solution of the noise constrained regularization problem. We present the numerical results of test problems, image restoration and medical imaging denoising. Our results indicate that the proposed Lagrange method is effective and efficient in computing good regularized solutions of ill-conditioned linear systems and in computing the corresponding Lagrange multipliers. Moreover, our numerical experiments show that the Lagrange method is computationally convenient. Therefore, the Lagrange method is a promising approach for dealing with ill-posed problems. This work was supported by the Italian FIRB Project “Parallel algorithms and Nonlinear Numerical Optimization” RBAU01JYPN.     

The sliding mode control for an airfoil system driven by harmonic and colored Gaussian noise excitations

This paper addresses a sliding mode control (SMC) for an airfoil model excited by a combination of harmonic force and colored Gaussian noise. Firstly, to reveal effects of random factors, the airfoil model with colored Gaussian noise is established. Next, via a perturbation technique and the stochastic averaging method, an analytical expression for the time-averaging mean square response is derived, which agrees well with results by Monte Carlo simulations. Additionally, we uncover that colored noise can induce a stochastic jump phenomenon, which can cause a catastrophic structural failure of the airfoil or even a disintegration of the aircraft. Subsequently, the SMC strategy is employed to design an effective controller for suppressing such a jump phenomenon of the stochastic airfoil system. In the case of the proposed stochastic airfoil system, we introduce concepts of ultimately reachability with an arbitrary small bound and a mean square practical stability to realize the reachability of the sliding mode and the stability of the system state. Finally, several numerical results are presented to demonstrate the effectiveness of the proposed SMC algorithm. We show that the jump phenomenon can be suppressed efficiently to avoid a catastrophic failure of the wing structure due to large deformation/deflection, and the energy cost is discussed to analyze the SMC approach.     

MPC for the Burgers Equation Based on an LQG Design

We consider optimal control problems for semilinear parabolic PDEs where process and measurement noise can occur. We discuss the solution of such problems by using a Model Predictive Control (MPC) strategy. For the resulting sub-problems we will use a Linear Quadratic Gaussian (LQG) design. Thus we will discuss the efficient implementation of the LQG approach since it is the major computational part in the MPC scheme for this class of optimal control problems. We will present some numerical results for the Burgers equation. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Model Predictive Control for Nonlinear Parabolic Differential Equations Based on a Linear Quadratic Gaussian Design

We consider optimal control problems for semilinear parabolic partial differential equations where process and measurement noise can occur. If we apply a Model Predictive Control (MPC) scheme we obtain optimal control problems on small time intervals. The resulting “smaller problems” can be linearized around a reference and solved by using a Linear Quadratic Gaussian (LQG) design. We present some theoretical background of the strategy above as well as results of a numerical implementation for a 3D problem. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)