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Covers sampling, transformations, acquisition models, aliasing problems, and examples in image processing.
Covers the sampling theorem, impulse train sampling, bandlimited signals, and the Nyquist rate.
Explores signals, instruments, and systems, covering ADC, Fourier Transform, sampling, signal reconstruction, aliasing, and anti-alias filters.
Explores sinusoidal aliasing, from periodic complex exponentials to aliasing of sinusoids.
Covers the concept of sampling, the sampling theorem, signal reconstruction, and the conversion of analogue signals to digital signals.
Covers syntax and typing rules in programming languages, discussing aliasing, mutability, and store locations.
Covers bandpass sampling for signals with limited frequency range, ensuring information preservation through proper sampling techniques.
Explores sampling signals and their spectrum, highlighting the significance of choosing the right sampling frequency for accurate signal representation.
