A Good Choice of Ridge Parameter with Minimum Mean Squared Error

Minimum mean-squared error covariance shaping

This paper develops and explores applications of a linear shaping transformation that minimizes the mean squared error (MSE) between the original and shaped data, i.e., that results in an output vector with the desired covariance that is as close as possible to the input, in an MSE sense. Three applications of minimum MSE shaping are considered, specifically matched filter detection, multiuser ...

Minimum mean squared error equalization using a priori information

A number of important advances have been made in the area of joint equalization and decoding of data transmitted over intersymbol interference (ISI) channels. Turbo equalization is an iterative approach to this problem, in which a maximum a posteriori probability (MAP) equalizer and a MAP decoder exchange soft information in the form of prior probabilities over the transmitted symbols. A number...

The Estimation Problem of Minimum Mean Squared Error

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...