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Time Varying (time + varying)
Selected AbstractsThe Output Effect of a Transition to Price Stability When Velocity Is Time VaryingJOURNAL OF MONEY, CREDIT AND BANKING, Issue 5 2010LYNNE EVANS price stability; velocity; disinflation; output boom; optimal speed of disinflation This paper explores the effect of time-varying velocity on output responses to policies for reducing/stopping inflation. We study a dynamic general equilibrium model with sticky prices in which we introduce time-varying velocity. Specifically, we endogenize time-varying velocity into the model developed by Ireland (1997) for analyzing optimal disinflation. The nonlinear solution method reveals that, depending on velocity, the "disinflationary boom" found by Ball (1994) may disappear even under perfect credibility and that early output losses may be much larger than previously thought. Indeed, we find that a gradual disinflation from a low inflation may even be undesirable. [source] Time varying and dynamic models for default risk in consumer loansJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 2 2010Jonathan Crook Summary., We review the incorporation of time varying variables into models of the risk of consumer default. Lenders typically have data which are of a panel format. This allows the inclusion of time varying covariates in models of account level default by including them in survival models, panel models or ,correction factor' models. The choice depends on the aim of the model and the assumptions that can be plausibly made. At the level of the portfolio, Merton-type models have incorporated macroeconomic and latent variables in mixed (factor) models and Kalman filter models whereas reduced form approaches include Markov chains and stochastic intensity models. The latter models have mainly been applied to corporate defaults and considerable scope remains for application to consumer loans. [source] Dynamic Textures for Image-based Rendering of Fine-Scale 3D Structure and Animation of Non-rigid MotionCOMPUTER GRAPHICS FORUM, Issue 3 2002Dana Cobza The problem of capturing real world scenes and then accurately rendering them is particularly difficult for fine-scale 3D structure. Similarly, it is difficult to capture, model and animate non-rigid motion. We present a method where small image changes are captured as a time varying (dynamic) texture. In particular, a coarse geometry is obtained from a sample set of images using structure from motion. This geometry is then used to subdivide the scene and to extract approximately stabilized texture patches. The residual statistical variability in the texture patches is captured using a PCA basis of spatial filters. The filters coefficients are parameterized in camera pose and object motion. To render new poses and motions, new texture patches are synthesized by modulating the texture basis. The texture is then warped back onto the coarse geometry. We demonstrate how the texture modulation and projective homography-based warps can be achieved in real-time using hardware accelerated OpenGL. Experiments comparing dynamic texture modulation to standard texturing are presented for objects with complex geometry (a flower) and non-rigid motion (human arm motion capturing the non-rigidities in the joints, and creasing of the shirt). Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Image Based Rendering [source] Adaptive robust H, state feedback control for linear uncertain systems with time-varying delayINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 9 2008Dan Ye Abstract This paper considers the problem of adaptive robust H, state feedback control for linear uncertain systems with time-varying delay. The uncertainties are assumed to be time varying, unknown, but bounded. A new adaptive robust H, controller is presented, whose gains are updating automatically according to the online estimates of uncertain parameters. By combining an indirect adaptive control method and a linear matrix inequality method, sufficient conditions with less conservativeness than those of the corresponding controller with fixed gains are given to guarantee robust asymptotic stability and H, performance of the closed-loop systems. A numerical example and its simulation results are given to demonstrate the effectiveness and the benefits of the proposed method. Copyright © 2008 John Wiley & Sons, Ltd. [source] Adaptive backstepping control for a class of time delay systems with nonlinear perturbationsINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 3 2008Chang-Chun Hua Abstract The sliding mode control method has been extensively employed to stabilize time delay systems with nonlinear perturbations. Although the resulting closed-loop systems have good transient and steady-state performances, the designed controllers are dependent on the time delays. But one knows that it is difficult to obtain the precise delay time in practical systems, especially when it is time varying. In this paper, we revisit the problem and use the backstepping method to construct the state feedback controller. First, a coordinate transformation is used to obtain a cascade time delay system. Then, a linear virtual control law is designed for the first subsystem. The memoryless controller is further constructed based on adaptive method for the second subsystem with the uncertainties bounded by linear function. By choosing new Lyapunov,Krasovskii functional, we show that the system state converges to zero asymptotically. Via the proposed approach, we also discuss the case that the uncertainties are bounded by nonlinear functions. Finally, simulations are done to verify the effectiveness of the main results obtained. Copyright © 2007 John Wiley & Sons, Ltd. [source] Robust H, control of uncertain linear impulsive stochastic systemsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 13 2008Wu-Hua Chen Abstract This paper develops robust stability theorems and robust H, control theory for uncertain impulsive stochastic systems. The parametric uncertainties are assumed to be time varying and norm bounded. Impulsive stochastic systems can be divided into three cases, namely, the systems with stable/stabilizable continuous-time stochastic dynamics and unstable/unstabilizable discrete-time dynamics, the systems with unstable/unstabilizable continuous dynamics and stable/stabilizable discrete-time dynamics, and the systems in which both the continuous-time stochastic dynamics and the discrete-time dynamics are stable/stabilizable. Sufficient conditions for robust exponential stability and robust stabilization for uncertain impulsive stochastic systems are derived in terms of an average dwell-time condition. Then, a linear matrix inequality-based approach to the design of a robust H, controller for each system is presented. Finally, the numerical examples are provided to demonstrate the effectiveness of the proposed approach. Copyright © 2007 John Wiley & Sons, Ltd. [source] A robust approach to the UAV task assignment problemINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 2 2008Mehdi Alighanbari Abstract This paper presents a new robust approach to the task assignment of unmanned aerial vehicles (UAVs) operating in uncertain dynamic environments for which the optimization data, such as target cost and target,UAV distances, are time varying and uncertain. The impact of this uncertainty in the data is mitigated by tightly integrating two approaches for improving the robustness of the assignment algorithm. One approach is to design task assignment plans that are robust to the uncertainty in the data, which reduces the sensitivity to errors in the situational awareness (SA), but can be overly conservative for long duration plans. A second approach is to replan as the SA is updated, which results in the best plan given the current information, but can lead to a churning type of instability if the updates are performed too rapidly. The strategy proposed in this paper combines robust planning with the techniques developed to eliminate churning. This combination results in the robust filter-embedded task assignment algorithm that uses both proactive techniques that hedge against the uncertainty, and reactive approaches that limit churning behavior by the vehicles. Numerous simulations are shown to demonstrate the performance benefits of this new algorithm. Copyright © 2007 John Wiley & Sons, Ltd. [source] Robust and efficient quantization and coding for control of multidimensional linear systems under data rate constraintsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 10-11 2007K. Li Abstract Recently, we reported results on coding strategies for scalar feedback systems with data-rate-limited feedback channels in which the data-rate constraints are time varying. Such rate-varying channels are typically encountered in communication networks in which links between nodes are subject to noise, congestion, and intermittent disruption. The present paper describes results of extending this research into the multidimensional domain. An important consideration is that for systems of dimension greater than one, many classical feedback designs cannot be realized for operation near the theoretical minimum possible data rate. A novel control coding scheme will be presented, and in terms of this, it will be shown that the advantages of coarse signal quantization that had been reported earlier for scalar systems remain in the multidimensional case. The key is to allocate the communication bandwidth efficiently among faster and slower modes. We discuss various strategies that allocate bandwidth by scheduling the time slots assigned to each mode. In particular, we propose a ,robust attention varying' technique, whose merit will be discussed in terms of its robustness with respect to time-varying communication channel capacity and also in terms of how well it operates when the feedback channel capacity is near the theoretical minimum data rate. Copyright © 2006 John Wiley & Sons, Ltd. [source] Model predictive control for constrained systems with uncertain state-delaysINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 17 2004Xiao-Bing Hu Abstract This paper presents a model predictive control (MPC) algorithm for a class of constrained linear systems with uncertain state-delays. Based on a novel artificial Lyapunov function, a new stabilizing condition dependent of the upper bound of uncertain state-delays is presented in an LMI (linear matrix inequality) form. The proposed MPC algorithm is developed by following the fashion of stability-enforced scheme. The new algorithm is then extended to linear time varying (LTV) systems with multiple uncertain state-delays. Numerical examples illustrate the effectiveness of the new algorithm. Copyright © 2004 John Wiley & Sons, Ltd. [source] A cross-coupling controller using an H, scheme and its application to a two-axis direct-drive robotJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 10 2002Ren-Wu Fang A cross-coupling controller (CCC) using an H, control scheme has been proposed to reduce the contouring error for a two-axis, direct-drive robot in tracking linear and circular contours effectively. Under the consideration that contour-tracking performance is a primary target over point-to-point tracking performance in a trajectory-tracking task, a CCC has been associated with joint controllers to reduce the contouring error by coordinating the motion of a two-axis robot arm. Contouring performance can thus be improved significantly. Furthermore, the proposed CCC design, which is a typical Multi-Input Multi-Output (MIMO) system with linear time varying (LTV) characteristics, has been verified as being internally stable. A USM (ultrasonic motor)-driven, two-axis, direct-drive robot is utilized to demonstrate the feasibility of the proposed scheme. Several experiments under various operating conditions are performed to validate its efficacy, and the results showed that the proposed scheme can reduce the contouring error significantly. © 2002 Wiley Periodicals, Inc. [source] Another look into the effect of premarital cohabitation on duration of marriage: an approach based on matchingJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2009Stefano Mazzuco Summary., The paper proposes an alternative approach to studying the effect of premarital cohabitation on subsequent duration of marriage on the basis of a strong ignorability assumption. The approach is called propensity score matching and consists of computing survival functions conditional on a function of observed variables (the propensity score), thus eliminating any selection that is derived from these variables. In this way, it is possible to identify a time varying effect of cohabitation without making any assumption either regarding its shape or the functional form of covariate effects. The output of the matching method is the difference between the survival functions of treated and untreated individuals at each time point. Results show that the cohabitation effect on duration of marriage is indeed time varying, being close to zero for the first 2,3 years and rising considerably in the following years. [source] The redshift distribution of absorption-line systems in QSO spectraMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 4 2007A. I. Ryabinkov ABSTRACT A statistical analysis of the space,time distribution of absorption-line systems (ALSs) observed in QSO spectra within the cosmological redshift interval z= 0.0,3.7 is carried out on the base of our catalogue of absorption systems (Ryabinkov et al. 2003). We confirm our previous conclusion that the z -distribution of absorbing matter contains non-uniform component displaying a pattern of statistically significant alternating maxima (peaks) and minima (dips). Using the wavelet transformation, we determine the positions of the maxima and minima and estimate their statistical significance. The positions of the maxima and minima of the z -distributions obtained for different celestial hemispheres turn out to be weakly sensitive to orientations of the hemispheres. The data reveal a regularity (quasi-periodicity) of the sequence of the peaks and dips with respect to some rescaling functions of z. The same periodicity was found for the one-dimensional correlation function calculated for the sample of the ALSs under investigation. We assume the existence of a regular structure in the distribution of absorption matter, which is not only spatial but also temporal in nature with characteristic time varying within the interval 150,650 Myr for the cosmological model applied. [source] The use of term structure information in the hedging of mortgage-backed securitiesTHE JOURNAL OF FUTURES MARKETS, Issue 7 2005Jason Fink This article examines the importance of term structure variables in the hedging of mortgage-backed securities (MBS) with Treasury futures. Koutmos, G., Kroner, K., and Pericli, A. (1998) find that the optimal hedge ratio is time varying; we determine the effect of yield levels and slopes on this variation. As these variables are closely tied with mortgage refinancing, intuition suggests them to be relevant determinants of the hedge ratio. It was found that a properly specified model of the time varying hedge ratio that excludes the level and slope of the yield curve from the information set would provide similar out-of-sample hedging results to a model in which term structure information is included. Thus, both the level of interest rates and the slope of the yield curve are unimportant variables in determining the empirically optimal hedge ratio between MBS and Treasury futures contracts. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:661,678, 2005 [source] THE PERFORMANCE OF DISCRETE LINEAR TIME VARYING CONTROL OF LINEAR PERIODIC PLANTSASIAN JOURNAL OF CONTROL, Issue 1 2004Jingxin Zhang ABSTRACT This paper analyzes the performance of discrete linear time varying (LTV) control of discrete linear periodically time varying (LPTV) plants for l2 disturbance rejection. It extends the results of [11,13] for linear periodic controllers to general LTV control of LPTV plants. It is shown that LPTV control provides strictly better control performance than linear strictly time varying control for LPTV plants. The analysis is carried out in frequency domain. This approach provides not only new results on disturbance rejection of LTV control but also some new insight into properties of general LTV systems. [source] Guaranteed Cost Sampled-Data Control for Refining ProcessASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, Issue 1-2 2001Yingquan Lu This paper presents a synthetic design procedure of guaranteed cost sampled-data control (GCSDC) for refining process. When a digital controller controls the refining process with appropriate sample and hold devices, the closed loop system is periodic time varying. Based on this sampled-data system, considering the uncertainties in the continuous-time plant, we define the guaranteed cost control and a controller that not only stabilizes the closed loop system but also guarantees an adequate level of the performance. Simulation results show that the control scheme is effective and practicable. [source] THE SYSTEMATIC RISK OF DEBT: AUSTRALIAN EVIDENCE,AUSTRALIAN ECONOMIC PAPERS, Issue 1 2005KEVIN DAVISArticle first published online: 21 FEB 200 This paper examines systematic risk (betas) of Australian government debt securities for the period 1979,2004 and makes three contributions to academic research and practical debate. First, the empirical work provides direct evidence on the systematic risk of government debt, and provides a benchmark for estimating the systematic risk of corporate debt which is relevant for cost of capital estimation and for optimal portfolio selection by asset managers such as superannuation funds. Second, analysis of reasons for non-zero (and time varying) betas for fixed income securities aids understanding of the primary sources of systematic risk. Third, the results cast light on the appropriate choice of maturity of risk free interest rate for use in the Capital Asset Pricing Model and have implications for the current applicability of historical estimates of the market risk premium. Debt betas are found to be, on average, significantly positive and (as expected) closely related, cross sectionally, to duration. They are, however, subject to significant time series variation, and over the past few years the pre-existing positive correlation between bond and stock returns appears to have vanished. [source] Structural Nested Mean Models for Assessing Time-Varying Effect ModerationBIOMETRICS, Issue 1 2010Daniel Almirall Summary This article considers the problem of assessing causal effect moderation in longitudinal settings in which treatment (or exposure) is time varying and so are the covariates said to moderate its effect.,Intermediate causal effects,that describe time-varying causal effects of treatment conditional on past covariate history are introduced and considered as part of Robins' structural nested mean model. Two estimators of the intermediate causal effects, and their standard errors, are presented and discussed: The first is a proposed two-stage regression estimator. The second is Robins' G-estimator. The results of a small simulation study that begins to shed light on the small versus large sample performance of the estimators, and on the bias,variance trade-off between the two estimators are presented. The methodology is illustrated using longitudinal data from a depression study. [source] Partly Functional Temporal Process Regression with Semiparametric Profile Estimating FunctionsBIOMETRICS, Issue 2 2009Jun Yan Summary Marginal mean models of temporal processes in event time data analysis are gaining more attention for their milder assumptions than the traditional intensity models. Recent work on fully functional temporal process regression (TPR) offers great flexibility by allowing all the regression coefficients to be nonparametrically time varying. The existing estimation procedure, however, prevents successive goodness-of-fit test for covariate coefficients in comparing a sequence of nested models. This article proposes a partly functional TPR model in the line of marginal mean models. Some covariate effects are time independent while others are completely unspecified in time. This class of models is very rich, including the fully functional model and the semiparametric model as special cases. To estimate the parameters, we propose semiparametric profile estimating equations, which are solved via an iterative algorithm, starting at a consistent estimate from a fully functional model in the existing work. No smoothing is needed, in contrast to other varying-coefficient methods. The weak convergence of the resultant estimators are developed using the empirical process theory. Successive tests of time-varying effects and backward model selection procedure can then be carried out. The practical usefulness of the methodology is demonstrated through a simulation study and a real example of recurrent exacerbation among cystic fibrosis patients. [source] | ||||||||||||||||