Considering a heterogeneous network (HetNet) system consisting of a macro tier overlaid with a second tier of small cells (SCs), this paper studies the mean square error (MSE) based precoding design to be employed by the macro base station and the SC nodes for multiple-input multipleoutput (MIMO) downlinks. First, a new sum-MSE of all users based minimization problem is proposed aiming to desig...

Three adaptive multichannel L-lters based on marginal data ordering are proposed. They rely on well-known algorithms for the iterative minimization of the mean square error (MSE), namely, the least mean squares (LMS), the normalized LMS (NLMS), and the LMS-Newton (LMSN) algorithms. We treat both the unconstrained minimization of the MSE and the minimization of the MSE when structural constraint...

porosity is one of the most important properties for comprehensive studies of hydrocarbon reservoirs. for determination of porosity in a rock, that is the ratio of volume of voids to the total volume of the rock, there are two conventional methods: in the first method, direct measurement of porosity is carried out by testing drilling cores. in the second method, porosity is determined indirectl...

This paper describes the automatic discovery, via an Evolution Strategy with Covariance Matrix Adaptation (CMAES), of vectors of real-valued coefficients representing matched forward and inverse transforms that outperform the 9/7 Cohen-Daubechies-Feauveau (CDF) discrete wavelet transform (DWT) for satellite image compression and reconstruction under conditions subject to quantization error. The...

The paper aims at contrasting two different ways of incorporating a-priori information in parameter estimation, i.e. hard-constrained and soft-constrained estimation. Hardconstrained estimation can be interpreted, in the Bayesian framework, as Maximum A-posteriori Probability (MAP) estimation with uniform prior distribution over the constraining set, and amounts to a constrained Least-Squares (...

Three novel adaptive multichannel L-filters based on marginal data ordering are proposed. They rely on well-known algorithms for the unconstrained minimization of the Mean Squared Error (MSE), namely, the Least Mean Squares (LMS), the normalized LMS (NLMS) and the LMS-Newton (LMSN) algorithm. Performance comparisons in color image filtering have been made both in RGB and U∗V ∗W ∗ color spaces. ...

Unconstrained lip-to-speech aims to generate corresponding speeches based on silent facial videos with no restriction head pose or vocabulary. It is desirable intelligible and natural speech a fast speed in unconstrained settings. Currently, handle the more complicated scenarios, most existing methods adopt autoregressive architecture, which optimized MSE loss. Although these have achieved prom...

This paper considers the problem of symbol detection in massive multiple-input multiple-output (MIMO) wireless communication systems. We consider hard-thresholding preceded by two variants regularized least squares (RLS) decoder; namely unconstrained RLS and with a box constraint, which is called Box-RLS. For all schemes, we focus on evaluation mean squared error (MSE) probability (SEP) for M-a...