The wavelet detection of the jump and cusp points of a regression function

1. IntroductionMuch effort has been taken to detect the change points of a noise contaminated signal. Detection of change points is very useful in dealing with practical problems such assignal analysis, image processing and phonetic identification. For example, in dealing withelect ro encep halogr am signal ? do ct ors of t en need t o find re al sharp cusp s which exhibi t t heaccelerations and decelerations in the beating of hearts. The early work on detection ofthe change points of a regres…     

Equilibrium point of Green's function for the annulus and Eisenstein series

We study the motion of the equilibrium point of Green's function and give an explicit parametrization of the unique zero of the Bergman kernel of the annulus. This problem is reduced to solving the equation , where is the usual Eisenstein series.

     

Filtering-based robust fault detection of fuzzy jump systems

This paper studies the robust fault detection filter (RFDF) design problems for uncertain nonlinear Markov jump systems with state delays and parameter uncertainties. By means of Takagi-Sugeno fuzzy models, the dynamics of filtering error generator and the fuzzy RFDF system are constructed. With the aid of the selected weighting matrix function, the design objective is to find an optimal RFDF which results in a minimal difference between the reference model (ideal solution) and the RFDF (real solution) to be designed. A sufficient condition is firstly established on the stochastic stability by using stochastic Lyapunov-Krasovskii functional approach. Then in terms of linear matrix inequalities techniques, sufficient conditions on the existence of fuzzy RFDF are presented and proved. Finally, the design problem is formulated as an optimization algorithm. Simulation results illustrate that the proposed RFDF can detect the faults shortly after the occurrences.     

Time series forecasting with neural network ensembles: an application for exchange rate prediction

This paper investigates the use of neural network combining methods to improve time series forecasting performance of the traditional single keep-the-best (KTB) model. The ensemble methods are applied to the difficult problem of exchange rate forecasting. Two general approaches to combining neural networks are proposed and examined in predicting the exchange rate between the British pound and US dollar. Specifically, we propose to use systematic and serial partitioning methods to build neural network ensembles for time series forecasting. It is found that the basic ensemble approach created with non-varying network architectures trained using different initial random weights is not effective in improving the accuracy of prediction while ensemble models consisting of different neural network structures can consistently outperform predictions of the single ‘best’ network. Results also show that neural ensembles based on different partitions of the data are more effective than those developed with the full training data in out-of-sample forecasting. Moreover, reducing correlation among forecasts made by the ensemble members by utilizing data partitioning techniques is the key to success for the neural ensemble models. Although our ensemble methods show considerable advantages over the traditional KTB approach, they do not have significant improvement compared to the widely used random walk model in exchange rate forecasting.     

Asymptotic normality for discretely observed Markov jump processes with an absorbing state

For a continuous-time Markov process, occasionally, only discrete-time observations are available. For a simple sample of homogeneous Markov jump processes with an absorbing state, observed each on a stochastic grid of time points, we establish asymptotic normality of the maximum likelihood estimator and close the gap in Kremer and Weißbach (2013). By showing that the solution of the Kolmogorov backward equation system is continuous differentiable, we can apply results for M-estimators.     

Boundedness of solutions for impulsive differential equations with integral jump conditions

The boundedness of solutions for certain nonlinear impulsive differential equations are obtained, the jumping conditions at discontinuous points are related to the integral of the past states, rather than a left hand limit at the discontinuous points. These results are obtained by new built impulsive integral inequalities with integral jumping conditions using the method of successive iteration.     

Robust H{infty} control for Markovian jump nonlinear systems

This paper deals with the robust H control problem of uncertainnonlinear stochastic systems with Markovian jump parameters.We assume that the uncertainties are structured such that suitablebounding functions can be found. A robust controller is thendesigned that will guarantee disturbance attenuation and asymptoticstability for all admissible uncertainties and L₂-bounded disturbances.The solution to the problem is characterized in terms of a setof smooth-positive semidefinite functions satisfying certainHamilton-Jacobi-Isaac (HJI) inequalities with some appropriatescaling functions. Both the case of matched and unmatched uncertaintiesare considered.     

On singular stochastic control and optimal stopping of spectrally negative jump diffusions

We consider a broad class of singular stochastic control problems of spectrally negative jump diffusions in the presence of potentially nonlinear state-dependent exercise payoffs. We analyse these problems by relying on associated variational inequalities and state a set of sufficient conditions under which the value of the considered problems can be explicitly derived in terms of the increasing minimal r-harmonic map. We also present a set of inequalities bounding the value of the optimal policy and prove that increased policy flexibility increases both the value of the optimal strategy as well as the rate at which this value grows.     

On evaluating the rate function of large deviations for jump processes

This is a sequel to our joint paper^[4] in which upper bound estimates for large deviations for Markov chains are studied. The purpose of this paper is to characterize the rate function of large deviations for jump processes. In particular, an explicit expression of the rate function is given in the case of the process being symmetrizable.     

Robust fault detection of Markovian jump systems with different system modes

This paper deals with the robust fault detection filter (RFDF) design problems for uncertain nonlinear Markovian jump systems with unknown input. By using a observer-based fault detection filter as residual generator, the RFDF design is formulated as an _H∞$H_{\infty }$-filtering problem. Particularly, two different Markov processes are considered for modeling the randomness of system matrix and the state delay. With the aid of the weighting matrix function, the design objective is to find an optimal RFDF, which results in a minimal difference between the reference model and the RFDF to be designed. By using a new convex polyhedron technique and two mode-dependent Lyapunov functional, some new sufficient conditions are established in terms of delay-dependent linear matrix inequalities (LMIs) to synthesize the residual generation scheme. Finally, a numerical example is given to illustrate the effectiveness of the proposed techniques.     

Hedging entry and exit decisions: optimizing location under exchange rate uncertainty

^** Email: alexru00{at}ms41.hinet.net^*** Email: ctlin{at}mail.yust.edu.tw The Cobb–Douglas production function with Abel's (1983,Am. Econ. Rev., 173, 228–233) model is extended herein,and real options analysis (ROA) for entry–exit decision-makingestablished utilizing Dixit's (1989b) decision model under exchangerate uncertainty. This work considers the effects of real exchangerates on strategies that determine the locations of productionby firms that are entering markets in two countries. The ROAis also adopted to evaluate the switching location between twocountries. A continuous-time model optimization problem is solvedin closed-form. This provides a useful beginning to an importantanalysis of the effects on industry of exchange rate fluctuationswhen the optimal entry (exit) trigger for transferring locationsis important for a basic global logistics model. Furthermore,a myopic solution of the optimal entry (exit) trigger, sensitivityanalysis and some characteristics of the optimal productionstrategy are sought. This paper contributes to the problem ofchoice of foreign production strategy.     

求解凸规划及鞍点问题定制的PPA 算法及其收敛速率

线性约束的凸优化问题和鞍点问题的一阶最优性条件是一个单调变分不等式. 在变分不等式框架下求解这些问题, 选取适当的矩阵G, 采用G- 模下的PPA 算法, 会使迭代过程中的子问题求解变得相当容易. 本文证明这类定制的PPA 算法的误差界有1/k 的收敛速率.     

Stochastic stability of positive Markov jump linear systems with fixed dwell time

This paper studies the stochastic stability of positive Markov jump linear systems with a fixed dwell time. By constructing an auxiliary system that originated from the initial system with state jumps, sufficient and necessary conditions of stochastic stability for positive Markov jump linear systems are obtained with both exactly known and partially known transition rates. The main idea in the latter case is applying a convex combination to convert bilinear programming into linear programming problems. On this basis, multiple piecewise linear co-positive Lyapunov functions are provided to achieve less conservative results. Then state feedback controller is designed to stabilize the positive Markov jump linear systems by solving linear programming problems. Numerical examples are presented to illustrate the viability of our conclusions.     

On heat kernel estimates and parabolic Harnack inequality for jump processes on metric measure spaces

In this paper, we discuss necessary and sufficient conditions on jumping kernels for a class of jump-type Markov processes on metric measure spaces to have scale-invariant finite range parabolic Harnack inequality.     

On determination of jumps in terms of Abel-Poisson mean of Fourier series

In this paper, we generalize some well-known results (Theorems A, C, and D) by establishing two general results (Theorems 1 and 3). As special applications, we find that the (generalized) jumps of f can be determined by the higher order partial derivatives of its Abel-Poisson means. This is different from the determination of jumps by higher order derivatives of the partial sums. We also give some estimates of the higher order partial derivatives of the Abel-Poisson mean of an integrable function F at those points at which F is smooth.     

On the fixed point sets of smooth involutions on the products of spheres

In this paper, we have, under some conditions on cohomology, that the fixed point set of a smooth involution on a product of spheres is of constant dimension.

     

On the branch point index of minimal surfaces

Let Γ be a closed, sufficiently smooth Jordan curve in and denote by the class of disk-type surfaces which map ∂B continuously and monotonically onto Γ. Then any minimal surface possesses only finitely many branch points in , and the order of any such point is well-defined, and also the index of an interior branch point is defined in a natural way if X is nonplanar. We show that also the index of boundary branch points can be defined if the curvature κ and the torsion τ of Γ are strictly nonzero. Secondly we derive upper bounds for the index of any branch point in terms of the total curvature of Γ or of its cut number. Dedicated to Professor Heinz K?nig on the occasion of his 80^th birthday     

On pricing of corporate securities in the case of jump-diffusion

Structural models of credit risk are known to present vanishing spreads at very short maturitiesThis shortcoming, which is due to the diffusive behavior assumed for asset values, can be circumvented by considering discontinuities of the jump type in their evolution over timeIn this paper, we extend the pricing model for corporate bond and determine the default probability in jump-diffusion model to address this issueTo make the problem clearly,we first investigate the case that the firm value follows a geometric Brownian motion under similar assumptions to those in Black and Scholes(1973), Briys and de Varenne(1997), i.e, the default barrier is KD(t, T) and the recovery rate is(1- ω), where D(t, T) is the price of zero coupon default free bond and ω is a constant(0 ω≤ 1)By changing the numeraire, we obtain the closed-form solution for both the price of bond and default probabilityFurther, we consider the case of jump-diffusion and suppose that a firm will go bankruptcy if its value Vt ≤ KD(t, T)and at the same time, the bondholder will receive(1- ω)Vt KBy introducing the Green function of PDE with absorbing boundary and converting the problem to an II-type Volterra integral equation, we get the closed-form expressions in series form for bond price and corresponding default probabilityNumerical results are presented to show the impact of different parameters to credit spread of bond.