Periodic signals hidden in noise may be detected by using
correlation techniques This thesis presents a study of how
correlation is approximated statistically, and carried out electronically.
The ability to detect periodic signals in noise, using correlation,
is justified mathematically in the first portion of the thesis.
The discussion is...
The purpose of this thesis is to apply the Canonical Correlation
Analysis (CCA) which belongs to the parametric methods for power
spectral estimation in the environments of either white noise or
colored noise. It is shown that optimal state space variables
belong to the range space of the canonical vectors...
Monte Carlo simulation is used to quantify and characterize uncertainty in a variety of applications such as financial/engineering economic analysis, and project management. The dependence or correlation between the random variables modeled can also be simulated to add more accuracy to simulations. However, there exists a difference between how correlation...