frequency, damping factor and amplitude of the mono-components are estimated through Yoshida’s algorithm and Hilbert’s transform …

Recently, we proposed a sampling algorithm for diffusion networks that locally adapts the number of nodes sampled … affect the tracking capability of the algorithm. In this paper, we propose a different solution, which automatically adjusts … are able to significantly improve the tracking capability of the original algorithm …

This paper proposes a color picture encryption algorithm with pixel restructuring and quick diffusion to coexist the … security and operational efficiency of the image encryption system. The algorithm employs a four-dimensional hyperchaotic … complexity of the algorithm and ensures the safety performance, but also improves the operating efficiency of the diffusion stage …

effect on their properties that are more useful to signal processing tasks. Rigorous analysis of our proposed LMSM algorithm …

urban infrastructures. Due to the widespread applications of the MUSIC algorithm in source localization, it is a suitable … solution in TomoSAR when multiple snapshots (looks) are available. While the classical MUSIC algorithm aims to estimate the … power spectrum. In this work, a new sequential MUSIC algorithm named recursive covariance canceled MUSIC (RCC-MUSIC), is …

greedy algorithm finds a solution on almost all instances with highprobability, explaining why most greedy algorithms work so …

The lattice reduction algorithm (LRA) takes as inputs a basis of lattice and outputs a relatively short vector up to … time of the algorithm is dominated by that of the applied LRA. Applying our technique to the Lenstra-- Lenstra …--Lov{\'a}sz (LLL)algorithm on lattice $L$ of rank $n$ and $\det(L)\le 2^{ n^2/4}$, we obtain a lattice vector of size $\le 2^{\sqrt …

combinations by using a backtracking process. The third algorithm directly generates the k-th sequence in the lexicographical order …

projected normalized least-mean-square (P-NLMS) algorithm is developed for solving this non-convex optimization problem. The P …-NLMS algorithm consists of two successive steps, i.e., adaptation and projection, where the adaptation step is based on the NLMS … algorithm followed by an Euclidean projection onto the non-convex feasible region, and they respectively are use to update and …