Loading...
Search for: signal-to-noise
0.014 seconds
Total 284 records

    Packet Loss Replacement in VOIP Using Linear Prediction Method

    , M.Sc. Thesis Sharif University of Technology Miralavi, Reza (Author) ; Ghorshi, Mohammad Ali (Supervisor) ; Mortazavi, Mohammad (Supervisor)
    Abstract
    In real-time packet-based communication systems one major problem is misrouted or delayed packets which result in degraded perceived voice quality. If some speech packets are not available on time, the packet is known as lost packet. The easiest task of a network terminal receiver is to replace silence for the duration of lost speech segments. In a high quality communication system in order to avoid quality reduction due to packet loss a suitable method and/or algorithm is needed to replace the missing segments of speech.There are several methods which have been proposed to reduce the effect of packet loss such as Waveform Substitution, High Order Autoregressive, Linear Prediction (LP),... 

    VoIP users’ Quality of Experience (QoE)Evaluation

    , Ph.D. Dissertation Sharif University of Technology Hesam Mohseni, Abdorreza (Author) ; Jahangir, Amir Hossein (Supervisor)
    Abstract
    Quality of Experience (QoE) indicates the overall quality of one service such as Voice over IP (VoIP) from users' point of view by considering several systems, human, and contextual factors. QoE measurement and prediction are more challenging than Quality of Service (QoS) which is only related to network parameters. There exist various objective and subjective methods for QoE prediction. This research investigates various features affecting QoE by proposing a comprehensive subjective evaluation by employing a large number of users. We show that many unconsidered factors including speaker specifications and signal properties, such as signal-to-noise ratio (SNR), can affect QoE so that the SNR... 

    Investigation of the Photonic Scattering Error in Radiography of Pipes and its Evaluation by Mote- carlo Simulation

    , M.Sc. Thesis Sharif University of Technology Masoumi Kolvanaq, Hojjat (Author) ; Vossoughi, Nasser (Supervisor) ; Movafeghi, Amir (Co-Advisor) ; Kermani, Abotaleb (Co-Advisor)
    Abstract
    Non-destructive testing method is for detect specimen flaws such as (crack, porosity, impure, welding defects, corrosion etc.) without destruction the specimen under inspection. Particular characteristic of radiography is an image product from specimen inside under testing where help to identity and better comprehend at flaw nature. Photon scattering is one of important factor to reduce image quality and signal to noise ratio. Scattered photons can due toexistent ingredient in the radiography environment and curvature of material transmission pipe where cause the disorder creation in the radiography images. In this research, pipe radiography simulated using the TIC and TIR radiography... 

    Efficiency Analysis of Principal Soft Computing Techniques for Noise Cancellation

    , M.Sc. Thesis Sharif University of Technology Ebrahimi, Naeim (Author) ; Banazadeh, Afshin (Supervisor)
    Abstract
    In this thesis, LMS, NLMS, RLS, ADALINE and ANFIS as five adaptive noise removal methods have been studied with a software application approach. The aim of this study is to obtain the best method to remove noise in terms of signal to noise ratio (SNR) improvement as well as the speed of convergence. In this regard, firstly by applying a frequency sweep input, which is contaminated with white noise, the performance of these algorithms are investigated. Then, an audio signal is utilized as the target input, and the performance of the corresponding algorithms have been analyzed in aspect of filter order and learning coefficient. The results show that by increasing the order of filter and... 

    Investigation and Implementation of Ultra High Speed Algorithms for Frequency Measurement

    , M.Sc. Thesis Sharif University of Technology Mahmoodi, Mohsen (Author) ; Pezeshk, Amirmansour (Supervisor) ; Sanaei, Esmaeel (Supervisor)
    Abstract
    The purpose of this project is to detect the instantaneous frequency of an unknown signal which has a frequency range from 2GHz to 18GHz, and its amplitude is limited. In the first step, this signal is amplified, and its amplitude is limited and then it is converted to a digital sequence using a mono-bit scheme and entered the FPGA through an ultra-fast serial port. After that, the algorithm of this project is supposed to do two main processing stages on the received stream of pulses. Detection should be performed in the first phase. It means that it should be determined whether the received pulse sequence is a random sequence made by noise or an almost regular sequence due to a sinusoidal... 

    Design and Fabrication of Self-biased High-Tc Superconducting Radiation Detector

    , M.Sc. Thesis Sharif University of Technology Yaghoubi, Mehdi (Author) ; Fardmanesh, Mehdi (Supervisor)
    Abstract
    A bolometer is a device for measuring electromagnetic waves, which uses the heating of a material with variable resistance to temperature. Due to the existing limitations and quality improvement, superconducting materials are used in the manufacture of these devices. In this dissertation, the construction and improvement of the components of a high temperature transient edge superconducting radiometer with terahertz detection capability is discussed. In the construction of these detectors, the superconducting material YBa2Cu3O7-x is used as a thermal sensor with a transition temperature of 93.5K. In order to characterize these detectors, an automatic system for measuring the voltage response... 

    Design and Implementation of Accurate Real-time Detection of Movement Intention Using Adaptive Wavelet Transform

    , M.Sc. Thesis Sharif University of Technology Chamanzar, Alireza (Author) ; Shabany, Mahdi (Supervisor) ; Sharifkhani, Mohammad ($item.subfieldsMap.e)
    Abstract
    The outlook of brain-computer interfacing (BCI) is very bright. The real-time, accurate detection of a motor movement task is critical in BCI systems. The poor signal-to-noise-ratio (SNR) of EEG signals and the ambiguity of noise generator sources in brain renders this task quite challenging. In this thesis, we demonstrate a novel algorithm for precise detection of the onset of a motor movement through identification of event-related-desynchronization (ERD) patterns. Using an adaptive matched filter technique implemented based on an optimized continues Wavelet transform by selecting an appropriate basis, we can detect single-trial ERDs. Moreover, we use a maximum-likelihood (ML),... 

    Design and Optimization of Magnetic Resonance Signal Detector to Enhancement of Sensitivity and SNR in Proton Precession Sensor

    , M.Sc. Thesis Sharif University of Technology Mazaheri Karvani, Jamal (Author) ; Fardmanesh, Mahdi (Supervisor)
    Abstract
    Proton precession is used in measurement of scalar magnetic field intensity. In this sensor, the magnetic field intensity is calculated through Larmor frequency using the proton precession frequency around the magnetic field. The accuracy of this sensor is in the range of picoTesla which is used for magnetic field measurement as well as the calibration of vector magnetic sensors. The signal to noise ratio in this sensor is due to the dimension and resistances of the wires and is a kind of RMS random noise. Although, changing the dimension of the wires for noise reduction and increasing the signal amplitude requires the fabrication of a bulky sensor with low power consumption. Therefore, it... 

    Photonic Generation of low Phase Noise Microwave Oscillation

    , Ph.D. Dissertation Sharif University of Technology Hosseini, Esmail (Author) ; Banai, Ali (Supervisor)
    Abstract
    Ultralow phase noise microwave oscillators with high stability are one of the key components required for many applications. With recent advances in ultrapure microwave oscillators, optoelectronic oscillators (OEOs) culminated in the state-of-the-art ultralow phase noise microwave oscillators. In this thesis, a nonlinear analytical approach is used to predict the main oscillation mode power and spurious levels in ultrapure microwave OEOs. Our analytical predictions are verified by numerical simulations and experimental data. Performance of an intensity-modulation direct-detection (IMDD) microwave photonic link (MWPL) operating under nonlinear conditions when its input consists of a sum of... 

    Digital Modulation Recognition of Communication Signals

    , M.Sc. Thesis Sharif University of Technology Hassanpour Zahraei, Salman (Author) ; Pezeshk, Amir Mansour (Supervisor) ; Behnia, Fereidoon (Co-Advisor)
    Abstract
    Modulation Recognition of communication signals has been an important theme in the field of wireless communication. Modulation Recognition has various applications for both military and civil purposes. Recently there has been considerable attention to Digital Modulation Recognition, due to the vast application of this kind of Modulation Recognition tasks. In this thesis, we proposed a Digital Modulation Recognition Algorithm, which is able to identify various types of digital modulations in low SNRs. These include BASK, BFSK, BPSK, 4-ASK, 4-FSK, 4-PSK, 8-FSK, 8-PSK, MQAM (M=16, 32, 64). The proposed method uses a general pattern recognition scheme, consisting of a feature extraction phase... 

    Design and Implementation of Proton Precession Magnetometer

    , M.Sc. Thesis Sharif University of Technology Kamrani, Mohammad Hamed (Author) ; Fardmanesh, Mahdi (Supervisor)
    Abstract
    Proton precession magnetometers are one of the most sensitive scalar magnetic sensors. Their function is based on Zeeman effect and also nuclear magnetic resonance phenomena. In this project we have designed and implemented needed coils, swithching and signal detection circuits. Because of extremely high sensitivity of this sensor to induced noises and also gradient of earth’s magnetic fileld, detection of precession signal needs design of low noise electronic circuits with special EMC considerations. The implemented system in this project contains different blocks, such as switching circuit and its related control unit, amplifier, filter and frequency meter. Using this system, the obtained... 

    Diversity and Error Probability Analysis and Determining the Effect of Non-Ideal Phase Estimation in Amplify-and-Forward and Beamforming Techniques

    , M.Sc. Thesis Sharif University of Technology Safavi, Ebrahim (Author) ; Hossein Khalaj, Babak (Supervisor)
    Abstract
    In this study we investigate the performance of amplify-and-forward (AF) and beamforming schemes in wireless networks. In our study we consider a general cooperative network consisting one transmit-receive pair and an arbitrary number of relays in which each relay has a separate power constraint. A two-step master-slave protocol is deployed in which at the first stage, relays listen to the transmitter and at the second stage, relays forward the recently received signal coherently. Main contributions of this dissertation are providing the exact closed-form of bit error rate analysis in the case of general AF networks, providing an integral-form upper bound of error probability of network... 

    Routing on Stochastic Geometric Graphs

    , Ph.D. Dissertation Sharif University of Technology Haji Mirsadeghi, Mir Omid (Author) ; Daneshgar, Amir (Supervisor) ; Baccelli, François (Supervisor)

    Receivers for diffusion-based molecular communication: Exploiting memory and sampling rate

    , Article IEEE Journal on Selected Areas in Communications ; Vol. 32, issue. 12 , 2014 , pp. 2368-2380 ; ISSN: 07338716 Mosayebi, R ; Arjmandi, H ; Gohari, A ; Nasiri-Kenari, M ; Mitra, U ; Sharif University of Technology
    Abstract
    In this paper, a diffusion-based molecular communication channel between two nano-machines is considered. The effect of the amount of memory on performance is characterized, and a simple memory-limited decoder is proposed; its performance is shown to be close to that of the best possible decoder (without any restrictions on the computational complexity or its functional form), using genie-aided upper bounds. This effect is adapted to the case of Molecular Concentration Shift Keying; it is shown that a four-bit memory achieves nearly the same performance as infinite memory for all of the examples considered. A general class of threshold decoders is considered and shown to be suboptimal for a... 

    Two layers beamforming robust against direction-of-arrival mismatch

    , Article IET Signal Processing ; Volume 8, Issue 1 , 2014 , Pages 49-58 ; ISSN: 17519675 Rahmani, M ; Bastani, M. H ; Shahraini, S ; Sharif University of Technology
    Abstract
    The presence of the desired signal (DS) in the training snapshots makes the adaptive beamformer sensitive to any steering vector mismatch and dramatically reduces the convergence rate. The objective of the present study is to propose a new adaptive beamformer which is robust against direction-of-arrival (DOA) mismatch and its convergence rate is not sensitive to the presence of the DS. This method is applicable to the arrays with specific structure such as the linear array. Our approach is based on the DS elimination from the training snapshots and the sub-array beamforming technique. To accomplish this goal, a blocking matrix which converts the primary data to the DS-free data is... 

    Adaptive handover algorithm in heterogeneous femtocellular networks based on received signal strength and signal-to-interference-plus-noise ratio prediction

    , Article IET Communications ; Volume 8, Issue 17 , 27 November , 2014 , Pages 3061-3071 ; ISSN: 17518628 Kalbkhani, H ; Yousefi, S ; Shayesteh, M. G ; Sharif University of Technology
    Abstract
    In this study, an efficient handover algorithm based on the received signal strength (RSS) prediction is presented for two-tier macro-femtocell networks in which, because of the fading effects of channel and short coverage range of femtocells, ping-pong handovers may take place. In the proposed approach, first each mobile station (MS) uses the recursive least square algorithm for predicting the RSS from the candidate base stations (BSs) including both femtocell and macrocell BSs. Then, according to the predicted RSS values, several future values of signal-to-interference plus noise ratio (SINR) are calculated. Afterwards, the candidate list of BSs is pruned according to the estimated future... 

    Robust and rapid converging adaptive beamforming via a subspace method for the signal-plusinterferences covariance matrix estimation

    , Article IET Signal Processing ; Vol. 8, Issue. 5 , July , 2014 , pp. 507-520 ; ISSN: 17519675 Rahmani, M ; Bastani, M. H ; Sharif University of Technology
    Abstract
    The presence of the desired signal (DS) in the training snapshots makes the adaptive beamformer sensitive to any steering vector mismatch and dramatically reduces the convergence rate. Even the performance of the most of the existing robust adaptive beamformers is degraded when the signal-to-noise ratio (SNR) is increased. In this study, a high converging rate robust adaptive beamformer is proposed. This method is a promoted eigenspace-based beamformer. In this paper, a new signal-plus-interferences (SPI) covariance matrix estimator is proposed. The subspace of the ideal SPI covariance matrices is exploited and the estimated covariance matrix is projected into this subspace. This projection... 

    Sparse representation-based super-resolution for diffusion weighted images

    , Article 21st Iranian Conference on Biomedical Engineering, ICBME ; 26-28 November , 2014 , pp. 12-16 ; ISBN: 9781479974177 Afzali, M ; Fatemizadeh, E ; Soltanian-Zadeh, H ; Sharif University of Technology
    Abstract
    Diffusion weighted imaging (DWI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain. However, clinical acquisitions are often low resolution. This paper proposes a method for improving the resolution using sparse representation. In this method a non-diffusion weighted image (bO) is utilized to learn the patches and then diffusion weighted images are reconstructed based on the trained dictionary. Our method is compared with bilinear, nearest neighbor and bicubic interpolation methods. The proposed method shows improvement in terms of Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM)  

    Sending a laplacian source using hybrid digital-analog codes

    , Article IEEE Transactions on Communications ; Vol. 62, issue. 7 , 2014 , p. 2544-2557 Abbasi, F ; Aghagolzadeh, A ; Behroozi, H ; Sharif University of Technology
    Abstract
    In this paper, we study transmission of a memoryless Laplacian source over three types of channels: additive white Laplacian noise (AWLN), additive white Gaussian noise (AWGN), and slow flat-fading Rayleigh channels under both bandwidth compression and bandwidth expansion. For this purpose, we analyze two well-known hybrid digital-analog (HDA) joint source-channel coding schemes for bandwidth compression and one for bandwidth expansion. Then we obtain achievable (absolute-error) distortion regions of the HDA schemes for the matched signal-to-noise ratio (SNR) case as well as the mismatched SNR scenario. Using numerical examples, it is shown that these schemes can achieve a distortion very... 

    Blind modal identification of structures from spatially sparse seismic response signals

    , Article Structural Control and Health Monitoring ; Vol. 21, issue. 5 , May , 2014 , p. 649-674 Ghahari, S. F ; Abazarsa, F ; Ghannad, M. A ; Celebi, M ; Taciroglu, E ; Sharif University of Technology
    Abstract
    Response-only identification of civil structureshas attracted much attention during recent years, as input excitations are rarely measurable for ambient vibrations. Although various techniques have been developed by which identification can be carried out using ambient responses, these techniques are generally not applicable to non-stationary excitations that structures experience during moderate-to-severe earthquakes. Recently, the authors proposed a new response-only modal identification method that is applicable to strong shaking data. This new method is highly attractive for cases in which the true input motions are unavailable. For example, when soil-structure interaction effects are...