Empirical mode decomposition (EMD) is a signal processing method that produces data-driven time-frequency representation suited to characterize time-varying and nonlinear phenomena. In EMD, intrinsic functions (IMF) are sequentially estimated from the of interest represent different oscilation modes produce an orthogonal original information. Different algorithms have been proposed for EMD esti...

‎Frames generalize orthonormal bases and allow representation of all the elements of the space‎. ‎Frames play significant role in signal and image processing‎, ‎which leads to many applications in informatics‎, ‎engineering‎, ‎medicine‎, ‎and probability‎. ‎In this paper‎, ‎we introduce the concepts of operator frame for the space $End_{mathcal{A}}^{ast}(mathcal{H})$ of all adjointable operator...

G-Frames in Hilbert spaces are a redundant set of operators which yield a representation for each vector in the space. In this paper we investigate the connection between g-frames, g-orthonormal bases and g-Riesz bases. We show that a family of bounded operators is a g-Bessel sequences if and only if the Gram matrix associated to its denes a bounded operator.

In this paper, the mechanical behaviors of bridges with unseating prevention devices in the superstructure were investigated. These devices can prevent bridge from unseating and divert most of the seismic forces from transferring to the bridge columns. The models of the rubber bearing, restrainer, and shear key were proposed and implemented into the SAP 2000 to obtain the seismic response of th...

let $g$ be a locally compact group, $h$ be a compact subgroup of $g$ and $varpi$ be a representation of the homogeneous space $g/h$ on a hilbert space $mathcal h$. for $psi in l^p(g/h), 1leq p leqinfty$, and an admissible wavelet $zeta$ for $varpi$, we define the localization operator $l_{psi,zeta} $ on $mathcal h$ and we show that it is a bounded operator. moreover, we prove that the localizat...

The performance of Hilbert spectrum (HS) in time-frequency representation (TFR) of audio signals is investigated in this paper. HS offers a fine-resolution TFR of time domain signals. It is derived by applying empirical mode decomposition (EMD), a newly developed data adaptive method for nonlinear and non-stationary signal analysis together with Hilbert transform. EMD represents any time domain...

Time-frequency distribution has received a growing utilization for analysis and interpretation of nonlinear and nonstationary processes in a variety of fields. Among them, two methods, such as, the empirical mode decomposition EMD with Hilbert transform HT which is termed as the Hilbert-Huang Transform HHT and the Hilbert spectrum based on maximal overlap discrete wavelet package transform MODW...