Thesis (M.A.)--California State University Channel Islands, 2009. / Submitted in partial fulfillment of the requirements for the degree of Masters Of Science in Mathematics. Title from PDF t.p. (viewed February 22, 2010).

No description available.

No description available.

A light scattering study of dilute solutions consisting of poly(4-vinylpyridine) dissolved in chloroform has been carried out. Chloroform is a good solvent for P4VP. Dynamic light scattering measurements show only a diffusion mode in the intensity autocorrelation function for freshly prepared solutions, but two modes are present as the solution ages. The two modes found in P4VP/CHCl3 solution both show a clear q dependence, q being the magnitude of the scattering wave vector, thus indicating that both are diffusive modes. For this system, the diffusion coefficient is found to be mainly determined by the osmotic modulus, with the solution stress modulus making a negligible contribution. A decrease of mutual diffusion coefficient with increasing polymer concentration is observed. As the temperature of the solution is lowered, the mutual diffusion coefficient decreases linearly. Extrapolation of the mutual diffusion coefficient to zero yields the critical temperature, at which the P4VP/CHCl3 solution undergoes a phase transition.

published_or_final_version / Mathematics / Master / Master of Philosophy

Thesis (M. Phil.)--University of Hong Kong, 1992.

Thesis (doctoral)--University of Tampere, 1983. / Extra t.p. with thesis statement inserted. Includes bibliographical references (p. 56-59).

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2007. / Includes bibliographical references (leaves 49-52). Also available in electronic version.

No description available.

Signal-to-noise ratio (SNR) estimation is one of the important research topics in wireless communications. In the receiver, many algorithms require SNR information to achieve optimal performance. In this thesis, an autocorrelation based SNR estimator is proposed. The proposed method utilizes the correlation properties of symbol sequence and the uncorrelated properties of noise sequence to distinguish the signal power from the received signal. Curve fitting method is used for SNR estimator to predict the signal power. Mean and variance performance of the proposed SNR estimator is compared with that of the conventional SNR estimator by computer simulations. These simulations consider additive white Gaussian noise and multipath Rayleigh fading channel with BPSK, 8PSK, 16QAM and 64QAM modulation schemes. According to the simulation results, the proposed method can provide better performance than conventional methods in both mean and mean-square-error.