Dual response surface optimization considers the mean and the variation simultaneously. The minimization of meansquared error (MSE) is an effective approach in dual response surface optimization. Weighted MSE (WMSE) is formed by imposing the relative weights, (k, 1−k), on the squared bias and variance components of MSE. To date, a few methods have been proposed for determining k. The resulting ...

Abstract: The minimum error entropy (MEE) algorithm is known to be superior in signal processing applications under impulsive noise. In this paper, based on the analysis of behavior of the optimum weight and the properties of robustness against impulsive noise, a normalized version of the MEE algorithm is proposed. The step size of the MEE algorithm is normalized with the power of input entropy...

In this paper, we propose a class of estimators for estimating the finite population mean of the study variable under Ranked Set Sampling (RSS) when population mean of the auxiliary variable is known. The bias and Mean Squared Error (MSE) of the proposed class of estimators are obtained to first degree of approximation. It is identified that the proposed class of estimators is more efficient as...

For an assignment, we investigate multiple features regarding Yelp reviews in order to construct a predictor for review star ratings. Our supervised learning model uses linear/ridge regression to observe the correlation between a set of features and review star ratings. Basic readily available features include the business’ star rating, the user’s average star rating, and the total number of vo...

This paper formulates and studies a general distributed field reconstruction problem using a dense network of noisy one–bit randomized scalar quantizers in the presence of additive observation noise of unknown distribution. A constructive quantization, coding, and field reconstruction scheme is developed and an upper–bound to the associated mean squared error (MSE) at any point and any snapshot...

To describe joint timeand frequency-selective (doublyselective) channels in mobile broadband wireless communications, we propose to use the finite parameter model based on the same Bessel functions for each tap (Bessel model). An expression of channel estimation mean squared error (MSE) based on the finite parameter models in Orthogonal Frequency Division Multiplexing (OFDM) systems is derived....

Abstract: In this paper, the economic design of MSE control chart is extended to the multivariate case. The important feature of this control chart is that it uses the target value instead of the process mean. According to Taguchi's viewpoint, any deviation from the target value represents a kind of loss. Therefore, we construct the model of economic design by considering not only the control c...

This paper presents two novel methods for Angle-of-Arrival (AoA) estimation in the presence of unknown mutual coupling. We mainly focus on the first method, where we show that this method could estimate AoAs of multiple sources when more mutual coupling parameters are included in the model, compared to existing methods. Furthermore, we derive a closed form Mean-Squared-Error (MSE) expression of...

BACKGROUND Indirect treatment comparison (ITC) and mixed treatment comparisons (MTC) have been increasingly used in network meta-analyses. This simulation study comprehensively investigated statistical properties and performances of commonly used ITC and MTC methods, including simple ITC (the Bucher method), frequentist and Bayesian MTC methods. METHODS A simple network of three sets of two-a...

In this study, the authors consider the min–max mean squared error (MSE)-based linear transceiver–relay design for multiple-input–multiple-output (MIMO) interference relay channel, where a finite number of half-duplex MIMO amplify and forward relays assist the communication between multiple source–destination pairs. The problem is formulated as minimising the maximum MSE among all data streams ...