Sharif Digital Repository

In this paper, we have developed an efficient method for obtaining an orthonormal wavelet that is matched to a given signal. The error between the wavelet and the given signal is minimized subject to the constraints of the amplitude and phase of the band-limited wavelet spectrum. To consider the constraints of the minimization problem, the Lagrange multipliers technique is applied. Variational method reduced the optimal matching problem to the solution of a set of functional equations for the amplitude and phase of the wavelet spectrum. Continuous functional equations were written in terms of Fourier coefficients of the phase of the transfer function of the quadrature low pass filter at the... 

This paper presents a new approach based on multi leader follower game in order to find the optimal contract price of distributed generation in distribution network considering competition among them. The leader problems correspond to the independent DG units who decide to maximize the individual profits, while the follower problem refers to the distribution company (DisCo) which seeks the minimization of the payments incurred in attending the expected demand while satisfying network constraints. Disco can purchase energy either from the transmission network through the substations or from the DG units within its network. The DisCo minimization problem acts as a constraint into the each DG... 

A novel algorithm for recovering the 3D shape of deformable objects purely from realistic monocular video is presented in this paper. Unlike traditional non-rigid structure from motion (NRSfM) methods, which have been studied only on synthetic datasets and controlled lab environments that needs some prior constraints (such as manually segmented objects, limited rotations and occlusions, or full-length trajectories), the proposed method has been described and tested on realistic video sequences, which have been downloaded from some social networks (such as Facebook and Twitter). In order to apply NRSfM to the realistic video sequences, because of no-prior information about the scene and... 

In recent studies, several methods have been suggested to decrease noise of magnetic resonance image (MRI) in order to raise the peak signal-to-noise ratio (PSNR) and the structural similarity index (SSIM). In this paper, we propose a novel method based on a minimization problem in Ripplet domain that uses singular value decomposition (SVD) in low rank learning to eliminate the noise of MRI images. We reschedule the weighted nuclear norm minimization (WNNM) problem in any edges of Ripplet domain transform and using an adaptive weighting structure to denoise the patches of Ripplet component matrix. The parameters of the proposed method are divided into two groups, some of them are calculated...