Sharif Digital Repository

Memories today expose an all-or-nothing correctness model thatincurs significant costs in performance, energy, area, and designcomplexity. But not all applications need high-precision storagefor all of their data structures all of the time. This these proposesmechan-isms that enable applications to store data approximately in a phase change memory main memoryand shows that doing so can improve the performance and reduce the power consumption by proposing two mechanisms. The First allows errors in multi-level cells by reducing the number ofprogramming pulses used to write them. The second mechanism reduces the number of error-prone patterns in the content of data block through a lightweith... 

The main goal of this work is solving system of linear equations Ax = b, where A is a n_n square matrix, b is a n_1 vector and x is the vector of unknowns. When n is large, using direct methods is not economical. Thus, the system is solved by iterative methods. At first, projection method onto subspace K _ Rn with dimension m _ n is described, and then this subspace K is equalized with the krylov subspace. Then,some samples of projection methods onto the krylov subspace, such as FOM, GMRES and CG (Conjugate Gradient), are considered. The preconditioning of the linear system is explained, that is, instead of solving system Ax = b, the system PAx = Pb (P nonsingular), is solved, such that the... 

Magnetic Resonance Imaging is one of the most advanced medical imaging procedure that noninvasively played in most applications. However, this imaging method is a good resolution, but not in the conventional high speed imaging method, in fact, the main problem is slow. In recent years many studies have been done to accelerate MRI that compressed sensing can be mentioned among them. Such methods, however, have had very good results but MRI systems are very complex. This project investigates the reconstruction of MR images using data from partial non-Cartesian samples aimed at reducing sampling time and also speed up the process of reconstruction of MR images have been studied. In this regard,... 

In many network which relationships between nodes are defined based on the similarity of attributes (Such as the World Wide Web and social networks), extracting information about networks object’s attributes may be difficult or even in many cases impossible.In these cases, predicting unknown attributes based on other objects attributes according to network structure can be extremely useful.Even more, finding a representative sample set of objects and trying to obtain their attributes in order to predict other object’s attributes with this obtained data can be an interesting problem. Finding such a set of objects with minimum size while giving maximizing accuracy in predicting other object’s... 

In this correspondence, a non-linear method of convergence accelerating and improving for iteration based algorithms is introduced. After convergence analysis, some enough conditions are proposed to guarantee convergence of the algorithm.For the sake of low complexity implementation of the proposed algorithm, some simple stabilizing methods are suggested. Simulation results show desirable performance of the proposed method and its capability to stabilize the iteration based algorithms. In the literature of missing samples recovery, the proposed method is applied to an Iterative Method (IM) as a general signal reconstruction method,then it is extended to the image recovery problem where... 

Increasing dynamics of mobile users intensifies the Doppler effect and degrades the performance of the communication system. Considering Fourier kernel-based modulation, in this research, we focus on dealing with the Doppler effect and compensating non-ideal communication channel response suffered from the Doppler-delay spread. In the first step, we study Zak transform and present a new transform for 2-D representation of time signals. This mapping is a well-known transformation that can be considered as a generalized discrete-time Fourier transform in the field of signal processing and can be used to represent a signal in the delay-Doppler domain. After providing a new 2-D transform, we... 

The main purpose of the thesis is Digital image Processing using the sparsity of image. The issue could be described in two ways. First is reconstruction of missed blocks of an image based on the sparsity of image in the transform domain and second is impulsive noise removal using the sparsity of noise in the spatial domain. In the first approach we will review Guleryuz method and simulate and analyze it. In the second approach, two new methods named RDE and Knockout will be introduced. These methods try two remove the impulsive noise of an image using its sparseness. RDE method is a development of conventional methods, but Knockout has a completely new idea. We will show that Knockout is... 

Direction Of Arrival (DOA) estimation or direction finding refers to determining the arrival angle of a planar wave impinging on the array of sensors or antennas. The DOA information can be used by the smart antenna system for beam-forming and reliable data transmission. The problem of DOA estimation in propagating plane waves played a fundamental role in many applications including acoustic, wireless communication systems, navigation, biomedical imaging, radar/sonar systems, seismic sensing, and wireless 911 emergency call locating. In the conventional DOA estimating systems, an array of elements (antennas or sensors) is used that are colocated in a uniform pattern called, Uniform Linear... 

Sensor Networks are set of devices which are distributed throughout an environment and are connected to each other, usually wirelessly, to collect environmental information including temperature, aire pressure, moist, pollution and physiological functions of the human body. Each device consists of a microprocessor, converter and power supply, transmitter and a receiver. In this study we intend to investigate such setup and the measured signals assuming they are sparse. A sparse signal is a discrete time signal most of indices of which are equal to zero. With this assumption at hand, we will be able to reduce the sampling rate and take advantage of sparse signal processing techniques. This... 

This thesis considers theoretical, analytical and engineering design issues relating to non-orthogonal Spectrally Efficient Frequency Division Multiplexing (SEFDM) communication systems that exhibit significant spectral merits when compared to Orthogonal FDM (OFDM) schemes. Alas, the practical implementation of such systems raises significant challenges, with the receivers being the bottleneck.
This research explores detection of SEFDM signals. The mathematical foundations of such signals lead to proposals of different orthonormalisation techniques as required at the receivers of non-orthogonal FDM systems. To address SEFDM detection, two approaches are considered: either attempt to...