A Kalman filter (KF) estimator has been formulated using a sequence of reduced-order models representing a whole batch behavior for providing the estimates of dynamic composition in a ternary batch distillation process operated in an optimal-reflux policy. A set of full-order models is firstly obtained by linearizing around different pseudo-steady state operating conditions along batch optimal ...

Wavelet shrinkage methods have been very successful in nonparametric regression. The most commonly used wavelet procedures achieve adaptivity through term-by-term thresholding. The resulting estimators attain the minimax rates of convergence up to a logarithmic factor. In the present paper, we propose a block thresholding method where wavelet coef-cients are thresholded in blocks, rather than i...

In an oil field that has reached its maximum gas handling capacity, and where wells are producing under gas coning conditions such that the gas-oil ratio (GOR) depends on the wells production rate, oil production is maximized if the marginal GOR (mGOR) is equal for all wells. The GOR and the mGOR are not readily available measurements, but they can be predicted using detailed reservoir models. ...

A new fusion approach of selecting an optimal bandwidth for re-substitution entropy estimator (RE) is presented in this study. When approximating the continuous entropy with density estimation, two types of errors will be generated: entropy estimation error (type-I error) and density estimation error (type-II error). These two errors are all strongly dependent on the undetermined bandwidths. Fi...

This paper investigates the optimal estimation problem for networked control systems, where the control packets are randomly dropped without acknowledgement to the estimator. Most existing results for this setup are concerned with the design of controller, while the optimal estimation and its performance evaluation have not been fully studied. This paper shows, unlike many other cases such as i...

In this paper we consider the problem of optimality in manifold reconstruction. A random sample Xn = {X1, . . . , Xn} ⊂ R composed of points lying on a d-dimensional submanifold M , with or without outliers drawn in the ambient space, is observed. Based on the Tangential Delaunay Complex [4], we construct an estimator M̂ that is ambient isotopic and Hausdorffclose to M with high probability. The...

Decoding neuronal information is important in neuroscience, both as a basic means to understand how neuronal activity is related to cerebral function and as a processing stage in driving neuroprosthetic effectors. Here, we compare the readout performance of six commonly used classifiers at decoding two different variables encoded by the spiking activity of the non-human primate frontal eye fiel...