Multi-Agent Estimation and Filtering for Minimizing Team Mean-Squared Error

Nonnegative mean squared prediction error estimation in small area estimation

Small area estimation has received enormous attention in recent years due to its wide range of application, particularly in policy making decisions. The variance based on direct sample size of small area estimator is unduly large and there is a need of constructing model based estimator with low mean squared prediction error (MSPE). Estimation of MSPE and in particular the bias correction of MS...

Mean-Squared Error Beamforming for Signal Estimation: A Competitive Approach

Beamforming is a classical method of processing temporal sensor array measurements for signal estimation, interference cancellation, source direction, and spectrum estimation. It has ubiquitously been applied in areas such as radar, sonar, wireless communications, speech processing, and medical imaging (see, for example, [1, 2, 3, 4, 5, 6, 7, 8] and the references therein.) Conventional approac...

Stochastic Image Denoising using Minimum Mean Squared Error (Wiener) Filtering

Digital images and video used for various tasks is often subject to distortion and noise. When information is known about the distortions and noise introduced into the image, their effects can be at least partially negated through image restoration techniques. In this paper, we explore the derivation of the inverse filter and the Wiener filter. We look and their efficacy in restoring images cor...

Root Mean Squared Error

• Predictive Accuracy Measures. These measures evaluate how close the recommender system came to predicting actual rating/utility values. • Classification Accuracy Measures. These measures evaluate the frequency with which a recommender system makes correct/incorrect decisions regarding items. • Rank Accuracy Measures. These measures evaluate the correctness of the ordering of items performed b...

The Estimation Problem of Minimum Mean Squared Error