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Lecture
The Fourier Transform
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Related lectures (32)
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The Sampling Theorem
Covers the sampling theorem, impulse train sampling, bandlimited signals, and the Nyquist rate.
Signals & Systems I: Sampling and Reconstruction
Explores ideal sampling, Fourier transformation, spectral repetition, and analog signal reconstruction.
Sampling and Reconstruction
Covers sampling, Fourier Transform, and reconstruction using low-pass filters in signal processing.
Fast Fourier Transform (FFT): Basics and Applications
Covers the Fast Fourier Transform (FFT) algorithm and its applications in computational physics, including image processing, experimental techniques, filters, and analysis of microscopy images.
Signal Processing: Sampling and Reconstruction
Covers Fourier transform, sampling, reconstruction, Nyquist frequency, and ideal signal reconstruction.
Signal Processing Fundamentals
Covers the basics of signal processing and electric circuits.
Signals & Systems II: Vector Analogy and Discrete Signals
Explores the link between DTFT, Z-transforms, and Fourier transforms, vector analogy, and discrete signals.
Fourier Series and Analysis
Covers Fourier series, analysis, the heat equation, Gibbs phenomenon, and Fourier transform properties.
Frequency Response of LTI Systems
Explores LTI systems, impulse response, convolution, system properties, and frequency response, including low-pass and band-pass filters.
Discrete Fourier Transform: Frequency Periodicity and Reconstruction
Explores frequency periodicity in the discrete Fourier transform for signal reconstruction.
