Sharif Digital Repository

Wireless sensor networks (WSNs) are tiny devices with limited computation and power supply. For such devices, data transmission is a very energy-consuming operation. Data aggregation eliminates redundancy and minimizes the number of transmissions in order to save energy. This research explores the efficiency of data aggregation by focusing on different aspects of the problem such as energy efficiency, latency and accuracy. To achieve this goal, we first investigate data aggregation efficiency with constraint on delay, which can be compatible with other important system properties such as energy consumption and accuracy. By simulation, we will show that, depending on the application, we can... 

Compressed Sensing (CS) technique refers to the digitalization process that efficiently reduces the number of measurements below the Nyquist rate while preserving signal structure. This technique was originally developed for the analysis of vector datasets. An x ∈R^n vector is transformed into an y ∈R^m vector so that n≪m. For a sufficient number of measurements, this transformation has been shown to preserve the signal structure. Therefore, the technique has been applied to machine learning applications.2D-CS was further developed for matrices (image datasets) so that they could be directly applied to matrices without flattening. X ∈R^(n×n) is transformed into Y ∈R^(m×m) via 2D-CD such... 

In this dissertation, different information networks such as Multiple-Access-Relay Network (MARN) and Broadcast-Relay Network (BRN) are introduced. MARN has one receiver, many relays and many senders. An achievable rate region is obtained for the MARN, using Partial Decode-and-Forward (PDF) strategy. In the case of semi-deterministic MARN, an outer bound and an inner bound to the capacity region are derived. BRN is a model with one sender, two relays and two receivers. Two different types of cooperation are considered for BRN: full cooperation and partial cooperation between relays. Inner bounds on the capacity region of BRN are obtained and compared with previous works. The main idea of the... 

By generalizing dictionary learning (DL) algorithms to Multidimensional (MD) mode and using them in applications where signals are inherently multidimensional, such as in three-dimensional (3D) Inverse Synthetic Aperture Radar (ISAR) imaging, it is possible to achieve much higher speed and less computational complexity. In this thesis, the formulation of the Multidimensional Dictionary Learning (MDDL) problem is expressed and six algorithms are proposed to solve it. The first one is based on the method of optimum directions (MOD) algorithm for 1D dictionary learning (1DDL), which uses alternating minimization and gradient projection approach. As the MDDL problem is non-convex, the second... 

Nowadays sharing data between users and organizations can be difficult due to privacy and legal reasons. Therefore, real-world data is not fully exploited by machine learning methods. A novel model training method called Federated Learning was proposed to alleviate the aforementioned problem by enabling users to jointly train learning models without sharing data. Federated learning utilization faces many challenges among which high communication cost, statistical heterogeneity and system heterogeneity are most important. This research deals with these challenges by proposing two methods of Reduced Clustering Federated Learning (RCFL) and Weighted Federated Distillation (WFD). Moreover, we... 

One of the most significant problems of oil regions is salinity of the produced water extracted from the well. Penetrating the produced water through the surrounding environments of the oil well in recent years, plenty of environmental problems, especially agricultural ones have been caused in these areas. According to the increasing trend of water salinity during the time, one of the urgent action in the oil industry of the country should be finding a way to reduce the amount of dissolved salt in the produced water. The purpose to this project has been representing a more appropriate configuration for desalination of the produced water. Therefore, the water sample containing less than 70000... 

Magnetic resonance imaging (MRI) is a highly efficient method that can provide acceptable contrast between soft tissues. But the big disadvantage of this method is that its acquisition is slow. To find the reason of being time-consuming should the procedure be surveyed. In the magnetic resonance imaging, location information obtained using phase and frequency encoding gradients. So the output is matrix of image data in the frequency domain, which is called k space. For the formation of the k space phase, need to apply gradients several times and this is the main reason of dullness of the system. Therefore, in this project using software methods try to reduce the scan time as possible. Among... 

Due to multiple transmit-receive channels, the signal model in a MIMO radar system is usually described by high dimensional data structures. However, the desired target space (e.g. range-azimuth domain) which shall be estimated, is mainly sparse (the number of existing targets is usually small). This observation has promoted the use of sparse recovery methods in multi-target detection and estimation in such radar systems which led to introducing the concept of compressive sensing (CS) based MIMO radars. Successful implementation of CS techniques for recovery of radar scenes (for target detection/estimation) from the received noisy measurements strongly entails that the associated sensing... 

One of the issues that today is considered by planners and system operators in power systems, especially the Iranian power grid, is the high variation and the lack of uniformity of load curves in different hours of the day. This has led to the use of all installed capacity of the country's production only in peak hours, and in the low and intermediate times, a large amount of installed capacity is out of the circuit, which means Unused capital. This problem is more or less seen in world power networks with high load variation curves. Also, the production of renewable energies has always been fluctuating, and the production of power control to improve this fluctuation is very important. This... 

Although up to now different processing algorithms have been proposed for Synthetic Aperture Radar (SAR) raw data, all of them suffer from one common problem and that is huge amount of data to be processed. So because of current system limitations, efficient compression algorithms for processing, saving, or transmitting data are needed. Up to now many algorithms have been proposed for SAR raw data compression, but each of them has some defects that should be payed attention to. The most important reason of these defects is the special characteristics of SAR images. With the aid of “Compressed Sensing (CS)”, the new field which has emerged recently, a special characteristic of the scene... 

The remote sensing is the knowledge of gaining information about an event without having direct access to it, and synthetic aperture radars (SAR) have gained spectacular attention in this filed due to their wide applications and high efficiency. The performance of SAR, which are classified in the space-borne or space-borne radars is similar to that of pulse radars. The transmitted signals in SAR are generally chirp signals, and the received signal is two-dimensional which is scattered in two dimensions of range and azimuth called as raw data. Due to relative movement between the radar base and the target point, the distance between the radar base and the target point would not be fixed along... 

The present paper discusses the possibility of adding recycled polymer fibres to high performance concrete (HPC). Fibres used in this study were recovered from discarded car timing belts. To investigate different characteristics of the concrete specimens several destructive and non-destructive tests, such as compressive strength, modulus of rupture, flexural toughness, ultrasonic velocity and electrical resistance tests were carried out. In addition, slump flow tests were conducted on the fresh concrete. Experimental results from the study showed that the use of low percentages (up to 0.5%) of waste fibres improved the modulus of rupture and flexural toughness. Based on ultrasonic and... 

Some researches have been carried out in the last 20 years in order to increase the present IC engines thermal efficiency and their optimum performance. (HCCI) engine is viewed as a combination of spark-ignition (SI) and compression-ignition (CI) engines. This is because HCCI engines use premixed fuel/air mixture like SI engines and have auto ignition combustion after the mixture is compressed like CI engines. Control of combustion and ignition timing are the main challenges of these engines. Ignition delay, compression ratio, fuel air equivalence ratio and intake temperature and pressure are considered to be the most effective parameters on HCCI combustion.HCCI engines have great potentials... 

According to needs for high quality pictures with high compression, in variety of applications such as Satellite communications, in this thesis some parts of JPEG2000 standard with computation and time complexity, have been implemented on FPGA. This parts are:
1- Two dimensional Discrete wavelet transform (2D-DWT)
2- Bit Plan Coding
3- Context-based Adaptive Binary Arithmetic Coding (MQ-Coder)
Each of these parts is implemented on basis of the best architectures in papers with some improvement on its hardware; and the results are compared with other similar works. Other parts, such as “Packet Creation” that are intrinsically software-based, are not implemented and it is... 

Recently, millimeter wave imaging (MMWI) technology is given more attention. This is as a result of three facts. First, despite the infrared or optical cameras, these systems can image a target, which is obscured by one or more optically barriers. Second, the electronics circuits in this band have seen great achievements in the current decade, which facilitate the implementation of MMWI structures. Third, there is no known health hazard for the systems operating in this band with moderate power. Therefore, in this project, a MMWI system based on compressed sensing (CS) for the concealed weapon detection application is proposed. This design consists of a linear antenna array, an appropriate... 

The main motivation behind compressive sensing is to reduce the sampling rate at the input of a discrete-time signal processing system. However, if for processing the sensed signal one requires to reconstruct the corresponding Nyquist samples, then the data rate will be again high in the processing stages of the overall system. Therefore, it is preferred that the desired processing task is done directly on the compressive measurements, without the need for the reconstruction of the Nyquist samples. This thesis addresses the cases in which the processing task is “detection and/or estimation”. Firstly, a detector/estimator is proposed for compressed sensing radars, which does not need to... 

Image processing is very important in several applications. Here we use a rectangular grid for image processing. Other approaches exist in the literature. One new approach is to change the grid from rectangular to hexagonal, due to its various advantages over the latter. Main advantage of the hexagonal structure in image processing is its resemblance with the arrangement of photoreceptors in the human eyes. The change in arrangement amounts to requiring less pixels. There is no inconsistency in pixel connectivity and thus angular resolution is higher in this arrangement. Our goal here is to study lossless compression algorithms for images with hexagonal pixels. First, we consider the... 

Monitoring of soil moisture plays an essential role in correct decision making and implementation of any closed loop control system in precision agriculture. On the one hand, continuous using of a lot of moisture sensors and monitoring of soil moisture via direct measurement is restricted by practical prohibitions. On the grounds that activation of a lot of sensors continuously requires communication of a large amount of information and causes high power consumption for a moisture monitoring system. On the other hand, using remote sensing methods such as satellite methods, for moisture monitoring in arbitrary spatial and time resolution for control purposes, is not practically possible. The... 

Compressive Sensing (CS) is a new paradigm in signal processing and information theory, which proposes to sample and compress sparse signals simultaneously and has drawn much attention in recent years. Many signals in lots of applications have a sparse representation in some bases, so CS is used as an efficient way of data compression in many applications such as image processing and medical applications in the last couple of years. Since some of the distributed information in complex networks are compressible too, CS can be used in order to gather the distribted information on the nodes or links efficiently. Traffic analysis and performance monitoring in computer networks, topology... 

The emerging field of compressed sensing deals with the techniques of combining the two blocks of sampling and compression into a single unit without compromising the performance. Clearly, this is not feasible for any general signal; however, if we restrict the signal to be sparse, it becomes possible. There are two main challenges in compressed sensing, namely the sampling process and the reconstruction methods. In this thesis, we will focus only on the deterministic sampling process as opposed to the random sampling. The sampling methods discussed in the literature are mainly linear, i.e., a matrix is used as the sampling operator. Here, we first consider linear sampling methods and...