<p> This thesis describes a proposed design of a special-purpose digital instrument that will obtain the first 32 coefficients of the Walsh-Fourier series of a low-fundamental frequency periodic voltage. The mathematics are developed for applying Walsh functions to obtain a Walsh-Fourier series in the same manner as sinusoidal waves are used to obtain a Fourier series of a periodic wave. It is shown how Walsh-Fourier coefficients are employed to obtain a Fourier series. Some familiar waveforms are shown as examples. The mathematical concepts are applied to the design of the instrument, of which two major portions have been constructed using integrated circuits. The Walsh-Fourier coefficients are available at the end of the second cycle of the input. The upper fundamental frequency limit of the instrument is approximately 60 Hz. There is no low-frequency limit.</p> / Thesis / Master of Engineering (MEngr)

Fourier analysis, Walsh-Fourier analysis, and wavelet analysis have often been used in time series analysis. Fourier analysis can be used to detect periodic components that have sinusoidal shape; however, it might be misleading when the periodic components are not sinusoidal. Walsh-Fourier analysis is suitable for revealing the rectangular trends of time series. The flaw of the Walsh-Fourier analysis is that Walsh functions are not periodic. The resulting Walsh-Fourier analysis is more difficult to interpret than classical Fourier analysis. Wavelet analysis is very useful in analyzing and describing time series with gradual frequency changes. Wavelet analysis also has a shortcoming by giving no exact meaning to the concept of frequency because wavelets are not periodic functions. In addition, all three analysis methods above require equally-spaced time series observations. In this dissertation, by using a sequence of periodic step functions, a new analysis method, adaptive Fourier analysis, and its theory are developed. These can be applied to time series data where patterns may take general periodic shapes that include sinusoids as special cases. Most importantly, the resulting adaptive Fourier analysis does not require equally-spaced time series observations. / Ph. D.