Sharif Digital Repository

The noise performance of intensity-modulation direct-detection microwave photonic links (MWPL) operating under large-signal conditions has been studied in this paper. A sinusoidal signal plus narrow-band white Gaussian noise is applied at the radio frequency input of the link, and the output spectrum is derived using a nonlinear analytical approach. We show that the output SNR can be severely affected by the interaction of signal and noise due to the nonlinearity of the MWPL combined with the large input modulating signal. It is shown that the large-signal noise figure (NF) of an MWPL depends on the input power, a dependence that is not readily apparent under small-signal conditions, due to... 

In this paper we develop a finite blocklength version of the Output Statistics of Random Binning (OSRB) framework. This framework is shown to be optimal in the point-to-point case. New second order regions for broadcast channel and wiretap channel with strong secrecy criterion are derived  

The current work deals with modification of the surface of a silica-polyamine with amine-based ionic liquid (IL) and its application for removal of Cu2+ from an aqueous media. The absorbent is simply prepared from commercially available reagents. The material is characterized by FT-IR spectroscopy, thermogravimetric analysis (TGA), N2 adsorption-desorption, and transmission electronic microscopy (TEM). Effects of several parameters on absorption efficiency, as well as activity of the absorbent to other metals, are also investigated. Moreover, the reusability of the absorbent is studied at the optimized condition. © The Royal Society of Chemistry 2016  

This article deals with analyzing the phase–frequency response of commande robuste d'ordre non-entier approximations of fractional-order differentiators. More precisely, an algebraic tight upper bound is derived for the phase of the approximations obtained from the commande robuste d'ordre non-entier method. Then, some applications for this achievement are discussed in the viewpoint of control systems analysis. These applications include usefulness of the obtained upper bound in stability preservation analysis during the commande robuste d'ordre non-entier–based approximation process and applicability of such a bound in finding necessary or sufficient conditions for test of positive... 

Blind source separation is an important field of study in signal processing, in which the goal is to estimate source signals by having mixed observations. There are some conventional methods in this field that aim to estimate source signals by considering certain assumptions on sources. One of the most popular assumptions is the non-Gaussianity of sources which is the basis of many popular blind source separation methods. These methods may fail to estimate sources when the distribution of two or more sources is Gaussian. Hence, this study aims to introduce a new approach in blind source separation for nonlinear and chaotic signals by using a dynamical similarity measure and relaxing... 

In this paper, a novel reinforcement learning method inspired by the way humans learn from others is presented. This method is developed based on cellular learning automata featuring a modular design and cooperation techniques. The modular design brings flexibility, reusability and applicability in a wide range of problems to the method. This paper focuses on analyzing sensitivity of the method's parameters and the applicability in optimization problems. Results of the experiments justify that the new method outperforms similar ones because of employing knowledge sharing technique, reasonable exploration logic, and learning rules based on the action trajectory  

The generalized belief propagation (GBP), introduced by Yedidia et al., is an extension of the belief propagation (BP) algorithm, which is widely used in different problems involved in calculating exact or approximate marginals of probability distributions. In many problems, it has been observed that the accuracy of GBP outperforms that of BP considerably. However, due to its generally higher complexity compared to BP, its application is limited in practice. In this paper, we introduce a stochastic version of GBP called stochastic generalized belief propagation (SGBP) that can be considered as an extension to the stochastic BP (SBP) algorithm introduced by Noorshams et al. They have shown... 

Non-invasive measurement of flow-mediated dilation (FMD) in the brachial artery for assessing endothelial function is costly and operator-dependent, limiting its application to research cases. In this paper, an approach based on a physiological model between normalized central blood pressure and finger photoplethysmogram is presented. Baseline model parameters are estimated using a genetic algorithm in 30 subjects consisting of ten normal blood pressure (BP), ten high-BP and ten elderly volunteers. Beat-to-beat fitness values after reactive hyperaemia are calculated using baseline (before cuff occlusion) data. Results show that stimulus-induced changes are fairly described with a first order... 

Naive Bayes (NB) classifier ease of use along with its remarkable performance has led many researchers to extend the scope of its applications to real-world domains by relaxing the conditional independence assumption of features given the information about the class variable. However, fulfilling this objective, most of the generalizations, cut their own way through compromising the model's simplicity, make more complex classifiers with a substantial deviation from the original one. Multi Independent Latent Component Naive Bayes Classifier (MILC-NB) leverages a set of latent variables to preserve the overall structure of naive Bayes classifier while rectifying its major restriction. Each... 

Naive Bayes (NB) classifier ease of use along with its remarkable performance has led many researchers to extend the scope of its applications to real-world domains by relaxing the conditional independence assumption of features given the information about the class variable. However, fulfilling this objective, most of the generalizations, cut their own way through compromising the model's simplicity, make more complex classifiers with a substantial deviation from the original one. Multi Independent Latent Component Naive Bayes Classifier (MILC-NB) leverages a set of latent variables to preserve the overall structure of naive Bayes classifier while rectifying its major restriction. Each... 

The design procedure and measured results of a novel 4 × 4 Butler matrix are presented in this paper. This asymmetrical structure provides fairly flexible phase outputs; therefore, the array radiation pattern can be rotated around the array normal axis. The structure of this modified Butler matrix is discussed in detail, and the explicit design formulas are derived to achieve the arbitrary main beams direction. Using the proposed design procedure, the Butler matrix can provide even broadside and endfire beams. In addition, this structure is employed to design two Butler matrices, which generate similar patterns as a conventional 8 × 8 Butler matrix, using only single layer circuits with...