Topical Outline:
1. Groundwork (Fourier's integral theorem, oddness and evenness, complex
conjugates, sine and cosine transforms, transforms in the limit)
2. Convolution (skill with graphical techniques, serial products, the
autocorrelation function, cross-correlation, energy spectrum)
3. Notation for Useful Functions (rectangle, triangle, Gaussian, etc.)
4. The Impulse Symbol (models, sifting property, sampling comb, null
functions, particularly well-behaved functions, generalized functions)
5. Basic Theorems (brief review of basic theorems of Fourier transform
theory)
6. The Two Domains (definite integral, moments, mean-square abscissa,
variance, smoothness and compactness, width measures, upper limits to
ordinate and slope, Schwarz's inequality, uncertainty relation,
central-limit theorem)
7. Sampling and Series (sampling theorem and variations, interpolation,
undersampling, ordinate and slope sampling, interlaced sampling, sampling
in the presence of noise, relation between Fourier series and Fourier
integral transform)
8. The Discrete Fourier Transform (relationship to continuous-domain
Fourier transform, cyclic convolution, application to real-world signals)
9. Dynamic Spectra and Wavelets (short-time amplitude spectra, Gabor
time-frequency analysis, time-frequency energy density function, Wigner
distribution, ambiguity function, wavelets and wavelet decomposition)
10. Relatives of the Fourier transform (Laplace, Hankel, Mellin, Abel, Z,
Hartley, and Hilbert transforms, analytic and complex signal
representations)
11. Two-dimensional Signals (2-D Fourier transform, polar coordinates
transform, 2-D sampling and replication, impulses in two dimensions)
12. Applications (antennas and optics, television image formation,
statistics and noise waveforms, heat conduction and diffusion)
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