The paper studies kernel regression learning from stochastic optimization and ill-posedness point of view. Namely, the convergence properties of kernel learning estimators are investigated under a gradual elimination of the regularization parameter with rising number of observations. We derive computable non-asymptotic bounds on the deviation of the expected risk from its best possible value an...

Data-based control design methods most often consist of iterative adjustment of the controller’s parameters towards the parameter values which minimize an H2 performance criterion. Typically, batches of input-output data collected from the system are used to feed directly a gradient descent optimization no process model is used. A limiting factor in the application of these methods is the lack ...

In this paper, we propose a robust speech detection algorithm with Heteroscedastic Discriminant Analysis (HDA) applied to the Time-Frequency Energy (TFE). The TFE consists of the log energy in time domain, the log energy in the fixed band 2503500 Hz, and the log Mel-scale frequency bands energy. The bottom-up algorithm with automatic threshold adjustment is used for accurate word boundary detec...

Polarized light carries information about the various physical parameters that have been acting upon it. Obtaining information on the observed object by studying the polarization of light reflected can be accomplished by several methods. The four Stokes parameters of the reflected light wave (S0, S1, S2, and S3) are generally estimated by observing the scene, with a CCD sensor, through a polari...

An adjustment scheme for the regularization parameter of a Moreau-Yosida-based regularization, or relaxation, approach to the numerical solution of pointwise state constrained elliptic optimal control problems is introduced. The method utilizes error estimates of an associated finite element discretization of the regularized problems for the optimal selection of the regularization parameter in ...

BACKGROUND AND OBJECTIVES Several dosage adjustment methods are currently available to individualize intravenous tobramycin dosing. This study compared different methods in terms of their recommendations for dosage adjustment, their estimation of patients' pharmacokinetic parameter values and their ability to predict subsequent observed tobramycin concentrations following once-daily tobramycin ...

An established rainfall-streamflow modelling methodology employing a six-parameter unit hydrograph-based rainfall-runoff model structure is developed further to give an improved model-fit to daily flows for the River Teifi at Glan Teifi. It is shown that a previous model of this type for the Teifi, which (a) accounted for 85% of the variance in observed streamflow, (b) incorporated a pure time ...

An adjustment scheme for the relaxation parameter of interior point approaches to the numerical solution of pointwise state constrained elliptic optimal control problems is introduced. The method is based on error estimates of an associated finite element discretization of the relaxed problems and optimally selects the relaxation parameter in dependence on the mesh size of discretization. The f...

The study is concerned with a single-parameter adaptive comb filter (ACF), a multi-notch filter with periodically located nulls. The filter is suggested to retrieve a waveform modeled by superposition of harmonics, in particular, periodic non-sinusoidal signal. Using trigonometric constraints between the signal fundamental frequency and over tones results in a non-linear estimation problem. In ...

Echocardiographic parameters can predict cardiovascular events in several clinical settings. However, which echocardiographic parameter is most predictive of each cardiovascular or non-cardiovascular event in patients starting hemodialysis remains unresolved. Echocardiography was used in 189 patients at the time of starting hemodialysis. We established primary outcomes as follows: cardiovascula...