A non-binary analog-to-digital converter (ADC) based on β-expansion, called β-encoder, is so far reported to achieve robustness against large process variation and wide environment change. Quantization error of β-encoder is not uniformly distributed, which makes the mean squared error (MSE) evaluation difficult. An analysis method for giving the upper bound of MSE of the quantization error is p...

In this paper, we present performance of pilot based channel estimation techniques such as Least Squares (LS) and Linear Minimum Mean Square Error (LMMSE) for different interpolation methods and modulation schemes. The performance is evaluated using the mean squared error (MSE) as the performance metric of interest for downlink LTE system. Simulation results show that for low SNR environment, a...

We study biased control variates (BCVs), whose purpose is to improve the efficiency of stochastic simulation experiments. BCVs replace the control-simulation mean with an approximation; the resulting control-variate estimator is biased. This bias may not be a significant issue for finite sample sizes, however, because our estimator minimizes the more general mean-squared-error (mse), i.e., the ...

• 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...

An alternative to extrinsic information transfer (EXIT) charts called mean squared error (MSE) charts that use a measure related to the MSE instead of mutual information is proposed. Using the relationship between mutual information and minimum mean squared error (MMSE), a relationship between the rate of any code and the area under a plot of MSE versus signal to noise ratio (SNR) is obtained, ...

An alternative to extrinsic information transfer (EXIT) charts called mean squared error (MSE) charts that use a measure related to the MSE instead of mutual information is proposed. Using the relationship between mutual information and minimum mean squared error (MMSE), a relationship between the rate of any code and the area under a plot of MSE versus signal to noise ratio (SNR) is obtained, ...

In this paper we consider a regression model and a general family of shrinkage estimators of regression coefficients. We derive the formula for the mean squared error (MSE) of the estimators for each individual regression coefficient. It is shown analytically that the usual shrinkage estimators are dominated by their positivepart variants in terms of MSE.

The increasing volatility in pricing and growing potential for profit in digital currency have made predicting the price of cryptocurrency a very attractive research topic. Several studies have already been conducted using various machine-learning models to predict crypto currency prices. This study presented in this paper applied a classic Autoregressive Integrated Moving Average(ARIMA) model ...

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 ...