In this dissertation a new time domain approach for the determination of material properties such as the complex permittivity and the complex permeability in a stripline geometry is presented. The new technique uses both Time Domain Reflectometry (TDR) and Time Domain Transmission (TDT) measurements for determining an optimum frequency dependent lossy transmission line model for the stripline under test. The optimization is done in the time domain by comparing the experimental TDR and TDT response waveforms with the simulated ones using a non-linear least squares fit. The conventional optimization algorithms have shown to be inefficient in this specific application. In this dissertation an efficient optimization algorithm which has been developed to suit this application is also presented. In general, the material properties in a stripline under test are related with the geometrical parameters of the line through complicated integral expressions. Using the proposed approach, the use of complicated integral expressions are avoided. The material properties such as the complex permittivity and the complex permeability are determined from the optimum lossy transmission line model. For this purpose, the frequency behavior of the line parameters have to be known beforehand in the form of causal mathematical models. The literature survey shows that, no causal model exists for the complex permittivity of thick film and polymer materials. The dissertation proposes a new causal model for this purpose. / Ph. D.

Effective and efficient system identification techniques for discrete, time domain, linear, MIMO, heavily damped modal systems from input/output sequences have been developed and simulated. This will facilitate a better understanding of the possible errors in the estimated model and lead to a more accurate compensator and estimator design. Three different time domain system identification algorithms have been developed in this work. The first algorithm determines the state space model in a pseudo controllable/observable canonical form. The second method is a computational simplification of the Eigensystem Realization Algorithm using pseudo observability and controllability indices. The third algorithm tested is the Pseudo Linear Identification Algorithm (PLID). The PLID algorithm is extensively tested on simulated data. This algorithm is also applied to identify a rectangular plate which gives a realistic idea of the identification capabilities of the PLID algorithm to real measured data. / Master of Science