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Lecture
Discrete Signals and Systems II: Fourier Transform Properties
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Related lectures (30)
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Signal Representations
Covers the properties of signal/data representations using Fourier transformations and matrices.
Fourier Transforms: Properties and Applications
Explores Fourier transforms, including properties, convolution, Parseval's theorem, and energy spectral density for non-periodic functions.
Properties of Fourier Transform
Explores the properties and applications of the Fourier transform in signal processing and mathematics.
Sampling: DT-time processing of CT signals
Covers the importance of sampling in signal processing, including the sampling theorem and signal reconstruction.
Fourier Transform: Concepts and Applications
Covers the Fourier transform, its properties, and applications in signal processing and differential equations, demonstrating its importance in mathematical analysis.
Image Processing II: DFT, DCT, and Wavelet Transforms
Explores eigenfaces, DFT, DCT, and wavelet transforms in image processing.
Convolution: Effect of Main Lobe
Explains the effect of convolving any spectrum by the Fourier transform of a rectangular window.
Fourier Transform and Sampling
Covers the Fourier transform of sampled signals, reconstruction, and harmonic response.
Discrete-Time Fourier Transform: Properties
Explores the properties of Discrete-Time Fourier Transform, including linearity, time and frequency shifts, time reversal, and convolution.
Spectrogram Analysis: Psychoacoustic Foundations & Signal Processing
Explores spectrogram analysis, including DFT, STFT, and CQT, for tasks like music transcription and onset detection.
