In this paper, the performance of different estimators in estimating the speech signal through Quantum parameters can be analyzed. The main objective is to estimate the speech signal by a set of linear and Non-linear estimators that are proposed to be efficient in performance. The Minimax mean square error estimator is designed to minimize the worst-case MSE. In an estimation context, the objec...

In this paper, the performance of the singleestimation (SE) and multiple-estimation (ME) is investigated in multiple-input multiple-output (MIMO) Rician flat fading channels using the traditional least squares (LS) estimator and the Bayesian minimum mean square error (MMSE) estimator. The closed form equations are obtained for mean square error (MSE) of the estimators in SE and ME cases under o...

This paper presents a novel data-driven approach to single channel speech enhancement employing Gaussian process (GP). Our approach is based on applying GP regression to estimate the residual gain with the input features being the a priori and a posteriori signal-to-noise ratios (SNRs). The residual gain is defined as the difference between the optimal gain and that obtained from the minimum me...

The present work addresses channel estimation based on the Minimum Mean Square Error (MMSE) and Least Square (LS) criteria and also considers time-domain channel statistics. It presents an optimal criterion for the pilots, and corresponding optimal designs enabling complexity reductions. Using a general model for a slowly fading channel, the MMSE and LS estimators and a method for modifications...

Reverse link feedback power control in subject to a feedback delay and in conjuction with diversity is considered over a frequency-nonselective slow Rayleigh fading channel. The transmission power of a mobile station is adjusted as a function of fed back estimated channel state information, so that the average error probability is minimized when the average transmission power is fixed. The chan...