No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

The Karhunen–Loève Transform (KLT) is prevalent nowadays in communication and signal processing. This thesis aims at attaining the KLT in the encoders and achieving the minimum sum rate in the case of Gaussian multiterminal source coding. In the general multiterminal source coding case, the data collected at the terminals will be compressed in a distributed manner, then communicated the fusion center for reconstruction. The data source is assumed to be a Gaussian random vector in this thesis. We introduce the rate-distortion function to formulate the optimization problem. The rate-distortion function focuses on achieving the minimum encoding sum rate, subject to a given distortion. The main purpose in the thesis is to propose a distributed KLT for encoders to deal with the sampled data and produce the minimum sum rate. To determine the distributed Karhunen–Loève transform, we propose three kinds of algorithms. The rst iterative algorithm is derived directly from the saddle point analysis of the optimization problem. Then we come up with another algorithm by combining the original rate-distortion function with Wyner's common information, and this algorithm still has to be solved in an iterative way. Moreover, we also propose algorithms without iterations. This kind of algorithms will generate the unknown variables from the existing variables and calculate the result directly.All those algorithms can make the lower-bound and upper-bound of the minimum sum rate converge, for the gap can be reduced to a relatively small range comparing to the value of the upper-bound and lower-bound. / Thesis / Master of Applied Science (MASc)

Ultra-wideband (UWB) communications is expected to revolutionize high data-rate, short-distance wireless communications, providing data-rates in excess of 100 Mbps. However, the wireless channel distorts the transmitted signal by dispersing the signal energy over time. This degrades the output signal-to-noise ratio (SNR) of a correlation based matched-filter receiver, limiting the achievable data-rate and user capacity. Most wideband channel models do not account for all the identified dispersion mechanisms namely the frequency dispersion, the resonant dispersion and the multipath dispersion. The objective of this research is to model resonant dispersion based on the Singularity Expansion Method (SEM) and provide guidelines for UWB receiver design to meet the data capacity. The original contribution of this research is a novel pole dispersion channel model that includes resonant dispersion characterization. An empirical investigation supports our claim that a correlation type matched-filter receiver using a template signal based on the pole dispersion channel model overcomes distortion related losses. Various physical mechanisms responsible for dispersion in UWB communication systems are described in detail. The applicability of the proposed dispersive channel model is evaluated using the optimal matched filter (OMF) receiver. The SEM approach, which was originally proposed for target identification using short pulse radars, offers limited benefits of due to its susceptibility to noise. A combined fuzzy-statistical approach is proposed to improve the robustness of resonant dispersion channel modeling in presence of noise. A natural extension of this doctoral research is to improve buried landmine detection as well as breast tumor detection by applying statistical and fuzzy analysis to the backscatter response. Moreover, radar target identification using UWB short pulses stands to gain tremendously from this research. / Ph. D.

This dissertation focuses on the modeling and control of WECS (Wind Energy Conversion System) in a multi-machine system. As one of the fastest growing renewable energy resources, the trend of wind energy changes to variable speed wind turbines. The concept of the variable speed is based on the variable speed according to the instantaneous wind speed of wind turbines. Since the utility grid requires the stable frequency and magnitude voltages, there must be grid interconnection of the wind farm and the utility grid. The grid interconnection must support the concept of the variable speed wind turbines. Since each wind turbine locates in a different location in a wind site, it receives the different wind speed. Hence the grid interconnection must convert the variable frequency and magnitude output voltages of the wind turbines to a synchronous frequency and magnitude voltages associated to the grid. With the new technologies of power semiconductor devices, the power converter can operate with high voltage, high current, and high switching frequency. This results in a higher power capacity of a wind farm. Nonetheless, the power converters generate harmonic distortions to the utility grid. The harmonic distortions components in the voltages and currents of the grid degrade the power quality. This results in the damage of electrical components in the power system such as capacitor banks, inductors, protection devices, etc. The harmonic distortions can be reduced with the technology of the multi-level inverter. It is required that the wind energy provides the real and reactive power control for frequency and voltage stability. In order to achieve the power control, the modeling and control of the power electronic grid interconnection is presented in this dissertation. The grid interconnection is modeled with linearization techniques. The models in frequency domain in the form of transfer functions are used to design the compensators in the control system. The model is considered as a SISO (Single Input Single Output) system to design the compensators in SISO tool of MATLAB. The selected control system is current control that can control the real and reactive powers independently. Furthermore, since the grid interconnection is modeled separately for each sub-system, the control system is verified with integration of the sub-systems. The grid interconnection is modeled in Simulink and simulated in the PSCAD. In reality, the power system is comprised of multi-machines. They affect the power system stability, reliability, and quality. The dynamic modeling of an aggregated wind farm with synchronous generator and grid interconnection in a multi-machine system is presented. The test system is a 10-bus system with three generators and three loads. The dynamic modeling involves the power flow calculations that determine the equilibrium points of the system. The system is modeled with differential equations of wind turbines, synchronous generators, and grid interconnection. The system is modeled in the time domain in state space form. The system characteristics can be determined by poles or eigen values obtained from the characteristic equations. Since the system is MIMO (Multi Input Multi Output) system, the optimal control theory is used to reduce the deviation of system behaviors during disturbances. The LQR (Linear Quadratic Regulator) is utilized to control the system with eigen value assignment method. Simulation results in Simulink are illustrated. / Ph. D.