Frequency Estimation Using Time-Frequency Based Methods

Any periodic signal can be decomposed into a sum of oscillating functions. Traditionally, cosine and sine segments have been used to represent a single period of the periodic signal (Fourier Series). In more general cases, each of these functions can be represented by a set of spectral parameters such as its amplitude, frequency, phase, and the variability of its instantaneous spectral components. The accuracy of these parameters depends on several processing variables such as resolution, noise level, and bias of the algorithm used. This thesis presents some background of existing frequency estimation techniques and proposes a new technique for estimating the instantaneous frequency of signals using short sinusoid-like basis functions. Furthermore, it also shows that the proposed algorithm can be implemented in a popular embedded DSPmicroprocessor for practical use. This algorithm can also be implemented using more complex features on more resourceful processing processors in order to improve estimation accuracy

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical Engineering

Year

2007

Author dc:creator

• Mai, Cuong

Contributors dc:contributor

• Charalampidis, Dimitrios
• Bourgeois, Edit
• Azzam, Rasheed

• frequency estimation
• oscillating functions
• Digital Signal Processing
• instantaneous spectral components
• instantaneous frequency
• periodic signal

Repository record dc:identifier

https://scholarworks.uno.edu/td/571

OAI identifier oai:identifier

oai:scholarworks.uno.edu:td-1571