We analyzed the effect of time and frequency domain windowing, or weighting, of the transmitted signal for least squares (LS) and minimum mean-square error (MMSE) estimators when the channel is time-variant. We considered the estimation error for different windows and we found that the windows can be selected independently. We explained the performance of the estimators with the help of the rad...

In this paper, the minimum mean-square error (MMSE) ˇ-order estimator for multichannel speech enhancement is proposed. The estimator is an extension of the single-channel MMSE ˇ-order and multichannel MMSE short-time spectral amplitude estimators using Rayleigh and Gaussian distributions for the statistical models under the assumption of a diffuse noise field where the noise is estimated indepe...

We consider the problem of signal estimation from a statistical mechanical perspective, using a relationship between the minimum mean square error (MMSE), of estimating a signal, and the mutual information between this signal and its noisy version. We derive several statistical-mechanical relationships between a few important quantities in this problem area, such as the MMSE, the mutual informa...

In this paper, the authors propose the Beta-Order Minimum Mean-Square Error (MMSE) Spectral Amplitude estimator with Chi statistical models for the speech priors. The new estimator incorporates both a shape parameter on the distribution and cost function parameter. The performance of the MMSE Beta-Order Spectral Amplitude estimator with Chi speech prior is evaluated using the Segmental Signal-t...

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...

The conventional decision feedback equalizer (DFE) separates the different signal classes using a single hyperplane. It is well known that the popular minimum mean square error (MMSE) design is generally not the optimal minimum bit error rate (MBER) solution. We propose a method of designing the separating hyperplane for the conventional DFE based on support vector machines (SVMs). The SVM desi...

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...

We derive a simple general parametric representation of the rate–distortion function of a memoryless source, where both the rate and the distortion are given by integrals whose integrands include the minimum mean square error (MMSE) of the distortion ∆ = d(X, Y ) based on the source symbol X , with respect to a certain joint distribution of these two random variables. At first glance, these rel...

{ This paper considers interference suppression , based on linear minimum mean square error (MMSE) ltering, in random code-division multiple-access (Random-CDMA) systems such as IS-95 and Wideband-CDMA using long pseudo-noise (PN) sequences. It examines the design of the MMSE receiver and its performance in terms of probability of bit error (Pe). Expressions for Pe are derived for systems with ...

This paper considers a ew class of time series models called Autoregressive Conditional Duration (ACD)models.Various statistical properties of this class of ACD models are given. A minimum mean square error (mmse)forecast function is obtained as it plays a important role in many practical applications.The theory is illustrated using a potential application based on financial data.