Sharif Digital Repository

In recent years with the increase of cellular phone subscribers, demand for high capacity networks is inevitable. For this reason, different methods have been proposed to increase the channel capacity. One method which has become popular in recent years is utilizing of Smart Antenna Systems. Smart antennas basically attempt to enhance the desired signal power and suppress the interferers by beamforming toward the DOA (direction-of-arrival) of the desired signal and nullsteering in the interferences’ DOAs. Smart Antennas first find the direction of signal sources, and then put the main gain toward the desired signal and put the nulls toward unwanted signals. As a result, we can obtain the... 

One of the most essential part of power system are transmission lines. Transmission of power from production centers to consumption centers is duty of these lines. Any disturbance in this duty make great losses to producers and consumers. One of the most disturbance in transmission lines are short circuits that occurred because of various causes. Most faults on transmission lines occurred in stormy weather that make more troubles for fault search. So we need a tool that can find location of fault precisely and quickly. This tool named fault locator. There are many algorithms for fault location and detection on power system transmission lines. These algorithms usually are dependent on very... 

This thesis investigates various modulation recognition systems both in analogue and digital forms. We are looking for a recognition technique considering practical implementation issues. To recognize the modulation, the career frequency is supposed to be known and a bandpass signal is received. Besides, we investigate some digital Automatic Modulation Recognition (AMR) methods. The techniques based on the features of the signal have less computational complexity compared to Maximum Likelihood (ML) techniques; hence they are more desirable for practical implementation. In this project, analog modulations are implemented using C++ software. For the convenience of users, here, two graphical... 

Disturbance rejection is one of the most important criteria that should be considered when designing control systems. The problem has been widely investigated and studied when the parameters of disturbance signal is known. However, there are still ongoing researches in the field when the parameters of disturbance signals are uncertain and/or varying with time. In some applications the disturbance signal can be modelled by special dynamics, e.g., step type disturbances with unknown magnitude, sinusoidal disturbances with unknown magnitude and frequency, and damped sinusoidal disturbances with unknown magnitude, frequency and damping factor. In such cases, an adaptive scheme for estimating the... 

Vehicle headway distribution plays an important role in various traffic engineering aspects such as capacity and level of service analysis and simulation issues. Although many headway models have been developed over the past decades, few have investigated the effects of vehicle’s type and its position in the traffic lanes on headway distributions. In this research, time headway data were collected at three different freeways using video camera. The collected data were analyzed and modeled for four different categories (i.e., car-car, car-truck, truck-car, and truck-truck) and under two traffic conditions of platooning and non-platoonig. Four types of probability distribution functions of... 

In this thesis, we investigate the statistical performance of the array processing algorithms. Theoretical performance analysis leads to better methods that outperform the existing algorithms. Besides, analytical performance analysis, results in a more profound understanding of the nature of the considered problem. First of all, problem of covariance matrix estimation, in the non-Gaussian signal case will be investigated. We will focus on a nonparametric estimator which relies on the sign of the data to estimate the covariance matrix on an element-by-element basis. It was known that, sign estimator may give invalid covariance estimates in higher dimensions of the data. We prove this fact in... 

Nowadays, all of the devices that measure blood pressure commercially at home are using wrist or arm cuffs preventing the systolic or diastolic blood pressure from being measured continuously. Various parameters such as blood flow with some degree of correlation with blood pressure that can be measured noninvasively have been suggested. However, these parameters do not produce accurate estimates for blood pressure. Pulse Transit Time (PTT) which is defined as the interval between the R peak of ECG signal and the next PPG signal valley has shown to have over 90% correlation with systolic blood pressure in past studies. In this thesis, the relationship between the value of the systolic blood... 

Due to extension of wireless networks, indoor positioning service becomes more important in new generations of WLAN networks. Complicated nature of indoor propagation channel decreases the quality of localization service in urban area. To overcome this problem, we surveyed characteristics of indoor radio channels and proposed methods to specify channel parameters to reduce its effect on positioning error. For this purpose, we introduce some super resolution methods and compare their precision and ability to implement on hardware. Among all of them, Matrix Pencil is selected and its mathematical functions are analyzed and stated in numerical algorithms and basic units. In implementain phase,... 

State estimation is a process in which values of unknown system state variables is obtained by considering measurements in such a system. State estimators’ output data are applied in control centers of power systems. Nowadays, using of phasor measurement unit (PMU) in WAMS (Wide Area Measurement Systems) and SCADA have significantly extended. PMUs increase the accuracy proportion compared with traditional measurement units, improve the power networks observability as well as detect and correct bad data. Since the possibility of removing the traditional measurement devices and replacing them with full PMU ones does not exist in the near future it is mandatory to find out an efficient and... 

Our problem is to evaluation state and form of a tracer passing through the vessel. Using this method, we can identify the effect of during used in some defected parts of body. This evaluation leads to in solving a Laplace equation with mixed boundary condition. Separating that problem, we reach to a collection of algebraic and linear equations. Solving this system, we approximate coefficients of the solution with a series the existence and uniqueness of and analytic solution has been proved using the Eigen functions finally, using numerical algorithms, we have interpreted the analytical solutions.
 

In this thesis, a reduced model of a distributed one-dimensional Solid Oxide Fuel Cell (SOFC) system is presented. Consequently the reduced model is used to estimate the states of the exact model. The reduced model is derived using the exact solution of the distributed model and implementing the Karhunen-Loève-Galerkin procedure. To achieve an exact solution of the distributed model, method of lines is used. In the method of lines, accuracy of the solution depends on the number of grid points. To increase the accuracy, the number of grid points should be increased which will lead to a high order dynamic model. Such a model is not suitable for state estimation, optimization or control... 

In this thesis one of the sensorless methods which exploits the existing anisotropies of the rotor is utilized to estimate rotor position. In order to implement this method, first a high frequency voltage is injected in a specific, time-varying direction and then the corresponding current response would be observed in order to estimate the rotor saliency position. The estimation of rotor position would be more precise as the magnetic anisotropy due to rotor saliency increases and as a result the effect of noise and different disturbances in estimation of rotor position would be decresed. The effect of stator resistence is one of these disturbances which is usually neglected as a result of... 

Error concealment is one of the effective ways to alleviate the effect of packet loss in video communication over error-prone environments. In order to estimate lost macro-blocks, we have employed Bayesian estimation as an efficient and robust framework. Gaussian process regression has been used as the modeling approach through this framework. Considering luminance component as Gaussian process,a minimum mean squared error estimation of the lost macro-block is obtained. This estimator, as a function of the existing data, is only determined by the covariance matrix defined over them. Therefore,the main step in Gaussian process regression, is construction of the convenient covariance matrix... 

Cost Estimation plays an essential and role in UAV (Unmanned Aerial Vehicles) Projects. By increasing the complexity of new unmanned systems, the importance of this task augments. Additionally, up to now, a comprehensive approach has not been adopted internationally. But in parallel a number of international companies and organizations has developed specific methods by themselves; confined to their corporate.
This project pursues developing a complexity-based model for cost estimation of unmanned aerial vehicles, especially Jet UAVs. However, it’s anticipated that this model may be utilized for all kind of systems, but it seems that jet UAVs use it with a better and more reliable... 

In this thesis, we investigate the problem of OFDM channel estimation exploiting channel sparsity. Due to the sparse nature of the scattering objects, most of wireless multipath channel have a sparse impulse response. Therefore it is possible to use the methods in the field of sparse signal processing for the purpose of estimating such channels for better accuracy, and efficient spectrum usage.
First of all the problem of OFDM channel estimation using scattered pilots is stated. Then the so-called IMAT methods together with the other sparse signal processing methods are used for the purpose of estimating channel nonzero taps. Furthermore, since efficient use of spectrum in... 

In this thesis, we intend to propose low cost SED-tolerant techniques for different compo­ nents of embedded processors core including data path components such as register file and ALU as well as control path components such as control unit. Since the reliability es­ timation is the essential step in design of a fault-tolerant system, we propose fast and accu­ rate analytical soft error rate (SER) estimation techniques in Section 4. The proposed techniques have the ability to measure: 1) the SER of a design; 2) the SER of each indi­ vidual gate and FF, and 3) the SER of a specific path in the design. Using such infor­ mation, designers can selectively protect the vulnerable parts... 

The aggressive device scaling and exponential increase in transistor counts on a chip have increasingly made the modern integrated circuits more susceptible to soft errors. Soft errors are caused by strikes from energetic particles such as neutrons and alpha particles. These errors are making a significant impact in the microelectronics industry. An essential step to design a highly reliable digital system with minimal performance and power penalty is Soft Error Rate (SER) estimation of system components.We propose a very fast and accurate analytical approach to estimate the overall SER and to identify the most vulnerable gates, flip-flops, and paths of a circuit. Our proposed approach fully... 

Cognitive Radio (CR), as a new concept to efficiently utilize a licensed spectrum, and this has received intensive attension in recent years. By applying the cognitive technique, an unlicensed user (the secondary user (SU)) is allowed to transmit at the Primary User’s (PU) spectrum band under some conditions. Different approaches have been introduced to be utilized by the SU in order to be able to efficiently transmit at the PR’s spectrum without any sustainsial destructive effects on PR transmission and reception, which one of them is using multiple antenna in the cognitive transmitter. Hereby, CR is able to increase its throughput without substansial harmfull effect on PR’ transmission by... 

In this research, we introduce a semi-supervised manifold regularization framework for hu- man pose estimation. Here we aim the three major challenges in discriminative human pose estimation. We utilize the unlabeled data to reduce the need to labeled data and compen- sate for the complexities in the input space. We model the underlying manifold by a nearest neighbor graph. Due to depth ambiguity which is the main challenge in this problem, the true underlying manifold of the data bends and gets too close to itself is some areas which results in poor graph construction. To solve this problem, we argue that the optimal graph is a subgraph of the k-nearest neighbor graph and employ an... 

Recently, sparse channel estimation, i.e. recovering a channel which has much less non zerotaps than its length using a known training sequence, has been a major area of research in the field of sparse signal processing. It can be shown that on the one hand, the underlying unique structure of such channels will make the possibility of estimating the channel taps with the extreme performance, i.e. achieving the Cram´er-Rao bound of the estimation. On the other hand, with an appropriate use of this structure, computational complexity of the receiver (both channel estimator and equalizer) can be reduced by an order. For achieving these goals in this thesis, firstly we have proposed an...