Adaptive thresholding methods have proved to yield high Signal-to-Noise Ratio (SNR) and fast convergence in finding the solution to the Compressed Sensing (CS) problems. Recently, It was observed that the robustness of a class of iterative sparse recovery algorithms such as Iterative Method with Adaptive Thresholding (IMAT) outperforms the well-known LASSO algorithm in terms of reconstruction q...

consider the following consistent sylvester tensor equation[mathscr{x}times_1 a +mathscr{x}times_2 b+mathscr{x}times_3 c=mathscr{d},]where the matrices $a,b, c$ and the tensor $mathscr{d}$ are given and $mathscr{x}$ is the unknown tensor. the current paper concerns with examining a simple and neat framework for accelerating the speed of convergence of the gradient-based iterative algorithm and ...

OBJECTIVE To evaluate the impact of the adaptive iterative dose reduction (AIDR) three-dimensional (3D) algorithm in CT on noise reduction and the image quality compared to the filtered back projection (FBP) algorithm and to compare the effectiveness of AIDR 3D on noise reduction according to the body habitus using phantoms with different sizes. MATERIALS AND METHODS Three different-sized pha...

This paper focuses on multi-target parameter estimation of multiple-input multiple-output (MIMO) radar with widely separated antennas moving platforms. Aiming at the superimposed signals caused by multi-targets, well-known expectation maximization (EM) is used in this paper. Target’s cross-section (RCS) spatial variations, different path losses and spatially-non-white noise appear because anten...

In this paper, we introduce and study a mixed variational inclusion problem involving infinite family of fuzzy mappings. An iterative algorithm is constructed for solving a mixed variational inclusion problem involving infinite family of fuzzy mappings and the convergence of iterative sequences generated by the proposed algorithm is proved. Some illustrative examples are also given.

This paper concerns power allocation in relay-assisted wireless channels for two-hop transmission. First, the transmitter sends the information to both the relay and receiver parts. Next, in the second hop, the transmitter cooperates with the relay to increase the received signal to noise ratio (SNR), assuming the relay makes use of the Amplify and Forward (AF) strategy. Moreover, it is assumed...

This paper presents an iterative signal enhancement algorithm for noise reduction in speech. The algorithm is based on a truncated singular value decomposition (SVD) procedure, which has already been used as a tool for signal enhancement [1][2]. Compared to the classical algorithms, the novel algorithm gives rise to comparable improvements in signal-to-noise ratio (SNR). Moreover the algorithm ...

This paper presents an iterative signal enhancement algorithm for noise reduction in speech. The algorithm is based on a truncated singular value decomposition (SVD) procedure, which has already been used as a tool for signal enhancement 1]]2]. Compared to the classical algorithms, the novel algorithm gives rise to comparable improvements in signal-to-noise ratio (SNR). Moreover the algorithm h...

A unicasting Ad hoc network is considered, where each node i is equipped with a receive/transmit beamformer pair (wi,gi). Each node’s SNR Γi satis£es Γi ≥ γ0. It is £rst shown that the minimum sum power beamformers for the network satisfy a weak duality condition, in which the pairs (g i ,w ∗ i ) achieve the same sum power as the primal network. However, the optimum receive beamformer wi is not...

In this paper, we introduce a new iterative algorithm for approximating a common solution of certain class of multiple-sets split variational inequality problems. The sequence of the proposed iterative algorithm is proved to converge strongly in Hilbert spaces. As application, we obtain some strong convergence results for some classes of multiple-sets split convex minimization problems.