We consider the approximately linear regression model E b 1x1 = I(x) 0 + f(x), XE S, where f(x) is a non-linear disturbance restricted only by a bound on its &(S) norm, and where S is the design space. For loss functions which are monotonic functions of the mean squared error matrix, we derive a theory to guide in the construction of designs which minimize the maximum (over f) loss. We then spe...

We introduce the Prediction Advantage (PA), a novel performance measure for prediction functions under any loss function (e.g., classification or regression). The PA is defined as the performance advantage relative to the Bayesian risk restricted to knowing only the distribution of the labels. We derive the PA for well-known loss functions, including 0/1 loss, cross-entropy loss, absolute loss,...

We present and discuss the theory of minimax Iand D-robust designs on a finite design space, and detail three methods for their construction that are new in this context: (i) a numerical search for the optimal parameters in a provably minimax robust parametric class of designs, (ii) a first-order iterative algorithm similar to that of Wynn (Ann Math Stat 5:1655–1664, 1970), and (iii) response-a...

The problem of minimum risk point estimation under squared-error loss function (SELF) for the parameter associated with the generalized life distributions, is considered. The failure of fixed sample size procedure is established. Sequential procedure using uniformly minimum variance unbiased estimator (UMVUE) at both the stopping and estimation stages is developed and the second-order approxima...

Recent years, compressive sensing (CS) has improved greatly for the application of deep learning technology. For convenience, the input image is usually measured and reconstructed block by block. This usually causes block effect in reconstructed images. In this paper, we present a novel CNN-based network to solve this problem. In measurement part, the input image is adaptively measured block by...

An amplify-and-forward (AF) wireless relay network consisting of a one-source-one-destination node pair and cooperative multiple N relay nodes is proposed in three adverse wireless communication environments, i.e., jamming, node geometry, and channel uncertainty. Based on the minimum mean square error (MMSE) criterion, the optimal amplifying relay matrix in three adverse wireless environments w...

Quality management is very important for many manufacturing industries. Process capability analysis has been widely applied in the field of quality control to monitor the performance of industrial processes. Hence, the lifetime performance indexC L is utilized to measure the performance of product, where L is the lower specification limit. This study constructs a Bayesian estimator of C L under...

Data collecting agents in large networks, such as the electric power system, need to share information (measurements) for estimating the system state in a distributed manner. However, privacy concerns may limit or prevent this exchange leading to a tradeoff between state estimation fidelity and privacy (referred to as competitive privacy). This paper builds upon a recent information-theoretic r...

Process capability indices PCIs aim to quantify the capability of a process of quality characteristic X tomeet some specifications that are related to ameasurable characteristic of its produced items. One such quality characteristic is life time of items. The specifications are determined through the lower specification limit L , the upper specification limit U , and the target value T . Maiti ...

Speech Enhancement is a challenging and important area of research due to the many applications that depend on improved signal quality. It is a pre-processing step of speech processing systems and used for perceptually improving quality of speech for humans. With recent advances in Deep Neural Networks (DNN), deep Denoising Auto-Encoders have proved to be very successful for speech enhancement....