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Estimation Schemes (estimation + scheme)
Selected AbstractsNONPARAMETRIC BOOTSTRAP PROCEDURES FOR PREDICTIVE INFERENCE BASED ON RECURSIVE ESTIMATION SCHEMES,INTERNATIONAL ECONOMIC REVIEW, Issue 1 2007Valentina Corradi We introduce block bootstrap techniques that are (first order) valid in recursive estimation frameworks. Thereafter, we present two examples where predictive accuracy tests are made operational using our new bootstrap procedures. In one application, we outline a consistent test for out-of-sample nonlinear Granger causality, and in the other we outline a test for selecting among multiple alternative forecasting models, all of which are possibly misspecified. In a Monte Carlo investigation, we compare the finite sample properties of our block bootstrap procedures with the parametric bootstrap due to Kilian (Journal of Applied Econometrics 14 (1999), 491,510), within the context of encompassing and predictive accuracy tests. In the empirical illustration, it is found that unemployment has nonlinear marginal predictive content for inflation. [source] New joint frame synchronisation and carrier frequency offset estimation method for OFDM systems,EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, Issue 4 2009Zhongshan Zhang We propose a new joint frame synchronisation and carrier frequency offset estimation scheme for burst transmission mode OFDM systems. This scheme uses a central-symmetric and comb-like (CSCL) training sequence, which eases the power detection at the receiver without increasing the total training sequence power. Fine frame synchronisation as well as carrier frequency offset acquisition with a maximum acquisition range of times the sub-carrier spacing can also be performed based on the proposed CSCL training sequence, where N is the discrete Fourier transform (DFT) length and SF is an integer-valued spreading factor used to generate CSCL. The post-acquisition residual carrier frequency offset can be further estimated and corrected via a fine adjustment algorithm. In order to reduce performance loss due to the high peak-to-average power ratio (PAPR) of the CSCL training sequence, a time-domain constant-envelope (CE) training sequence is also proposed. The superior estimation accuracy of the proposed algorithm over that of the Moose algorithm and the SS (Shi and Serpedin) algorithm is proved by computer simulation. Copyright © 2008 John Wiley & Sons, Ltd. [source] Robust diagnosis and fault-tolerant control of distributed processes over communication networksINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 8 2009Sathyendra Ghantasala Abstract This paper develops a robust fault detection and isolation (FDI) and fault-tolerant control (FTC) structure for distributed processes modeled by nonlinear parabolic partial differential equations (PDEs) with control constraints, time-varying uncertain variables, and a finite number of sensors that transmit their data over a communication network. The network imposes limitations on the accuracy of the output measurements used for diagnosis and control purposes that need to be accounted for in the design methodology. To facilitate the controller synthesis and fault diagnosis tasks, a finite-dimensional system that captures the dominant dynamic modes of the PDE is initially derived and transformed into a form where each dominant mode is excited directly by only one actuator. A robustly stabilizing bounded output feedback controller is then designed for each dominant mode by combining a bounded Lyapunov-based robust state feedback controller with a state estimation scheme that relies on the available output measurements to provide estimates of the dominant modes. The controller synthesis procedure facilitates the derivation of: (1) an explicit characterization of the fault-free behavior of each mode in terms of a time-varying bound on the dissipation rate of the corresponding Lyapunov function, which accounts for the uncertainty and network-induced measurement errors and (2) an explicit characterization of the robust stability region where constraint satisfaction and robustness with respect to uncertainty and measurement errors are guaranteed. Using the fault-free Lyapunov dissipation bounds as thresholds for FDI, the detection and isolation of faults in a given actuator are accomplished by monitoring the evolution of the dominant modes within the stability region and declaring a fault when the threshold is breached. The effects of network-induced measurement errors are mitigated by confining the FDI region to an appropriate subset of the stability region and enlarging the FDI residual thresholds appropriately. It is shown that these safeguards can be tightened or relaxed by proper selection of the sensor spatial configuration. Finally, the implementation of the networked FDI,FTC architecture on the infinite-dimensional system is discussed and the proposed methodology is demonstrated using a diffusion,reaction process example. Copyright © 2008 John Wiley & Sons, Ltd. [source] Cell Population Modeling and Parameter Estimation for Continuous Cultures of Saccharomyces cerevisiaeBIOTECHNOLOGY PROGRESS, Issue 5 2002Prashant Mhaskar Saccharomyces cerevisiae is known to exhibit sustained oscillations in chemostats operated under aerobic and glucose-limited growth conditions. The oscillations are reflected both in intracellular and extracellular measurements. Our recent work has shown that unstructured cell population balance models are capable of generating sustained oscillations over an experimentally meaningful range of dilution rates. A disadvantage of such unstructured models is that they lack variables that can be compared directly to easily measured extracellular variables. Thus far, most of our work in model development has been aimed at achieving qualitative agreement with experimental data. In this paper, a segregated model with a simple structured description of the extracellular environment is developed and evaluated. The model accounts for the three most important metabolic pathways involved in cell growth with glucose substrate. As compared to completely unstructured models, the major advantage of the proposed model is that predictions of extracellular variables can be compared directly to experimental data. Consequently, the model structure is well suited for the application of estimation techniques aimed at determining unknown model parameters from available extracellular measurements. A steady-state parameter selection method developed in our group is extended to oscillatory dynamics to determine the parameters that can be estimated most reliably. The chosen parameters are estimated by solving a nonlinear programming problem formulated to minimize the difference between predictions and measurements of the extracellular variables. The efficiency of the parameter estimation scheme is demonstrated using simulated and experimental data. [source] Joint data detection and estimation of time-varying multipath rayleigh fading channels in asynchronous DS-CDMA systems with long spreading sequences,EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, Issue 2 2007Pei Xiao In this paper, we present a joint approach to data detection and channel estimation for the asynchronous direct-sequence code-division multiple access (DS-CDMA) systems employing orthogonal signaling formats and long scrambling codes. Our emphasis is placed on different channel estimation algorithms since the performance of a communication system depends largely on its ability to retrieve an accurate measurement of the underlying channel. We investigate channel estimation algorithms under different conditions. The estimated channel information is used to enable coherent data detection to combat the detrimental effect of the multiuser interference and the multipath propagation of the transmitted signal. In the considered multiuser detector, we mainly use interference cancellation techniques, which are suitable for long-code CDMA systems. Interference cancellation and channel estimation using soft estimates of the transmitted signal is also proposed in this paper. Different channel estimation schemes are evaluated and compared in terms of mean square error (MSE) of channel estimation and bit error rate (BER) performance. Based on our analysis and numerical results, some recommendations are made on how to choose appropriate channel estimators in practical systems. Copyright © 2006 AEIT [source] Feedforward joint phase and timing estimation for MSK,type signalsEUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, Issue 4 2001Michele Morelli Novel non data,aided (NDA) algorithms are proposed for joint estimation of timing and carrier phase in MSK,type modulations. They are based on maximum likelihood methods and have a feedforward structure which is suitable to fully digital implementation. Performance with MSK and Gaussian MSK. (GMSK) is assessed by computer simulations and compared with that of other existing estimation schemes. [source] Pressure and temperature-based adaptive observer of air charge for turbocharged diesel enginesINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 6 2004A. G. Stefanopoulou Abstract In this paper we design an adaptive air charge estimator for turbocharged diesel engines using intake manifold pressure, temperature and engine speed measurements. This adaptive observer scheme does not depend on mass air flow sensors and can be applied to diesel engines with no exhaust gas recirculation (EGR). The performance of the adaptive scheme is shown in simulations to be comparable to conventional air charge estimation schemes if perfect temperature measurements are available. The designed scheme cannot estimate fast transients and its performance deteriorates with temperature sensor lags. Despite all these difficulties, this paper demonstrates that (i) the proposed scheme has better robustness to modelling errors because it provides a closed-loop observer design, and (ii) robust air charge estimation is achievable even without air flow sensors if good (fast) temperature sensors become available. Finally, we provide a rigorous proof and present the implementation challenges as well as the limiting factors of this adaptation scheme and point to hardware and temperature sensor requirements. Copyright © 2004 John Wiley & Sons, Ltd. [source] Anisotropy in high angular resolution diffusion-weighted MRI ,MAGNETIC RESONANCE IN MEDICINE, Issue 6 2001Lawrence R. Frank Abstract The diffusion in voxels with multidirectional fibers can be quite complicated and not necessarily well characterized by the standard diffusion tensor model. High angular resolution diffusion-weighted acquisitions have recently been proposed as a method to investigate such voxels, but the reconstruction methods proposed require sophisticated estimation schemes. We present here a simple algorithm for the identification of diffusion anisotropy based upon the variance of the estimated apparent diffusion coefficient (ADC) as a function of measurement direction. The rationale for this method is discussed, and results in normal human subjects acquired with a novel diffusion-weighted stimulated-echo spiral acquisition are presented which distinguish areas of anisotropy that are not apparent in the relative anisotropy maps derived from the standard diffusion tensor model. Magn Reson Med 45:935,939, 2001. Published 2001 Wiley-Liss, Inc. [source] Supervised classification and tunnel visionAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 2 2005David J. Hand Abstract In recent decades many highly sophisticated methods have been developed for supervised classification. These developments involve complex models requiring complicated iterative parameter estimation schemes, and can achieve unprecedented performance in terms of misclassification rate. However, in focusing efforts on the single performance criterion of misclassification rate, researchers have abstracted the problem beyond the bounds of practical usefulness, to the extent that the supposed performance improvements are irrelevant in comparison with other factors influencing performance. Examples of such factors are given. An illustration is provided of a new method which, for the particular problem of credit scoring, improves a relevant measure of classification performance while maintaining interpretability. Copyright © 2005 John Wiley & Sons, Ltd. [source] | ||||||||||