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Lecture
The Discrete Fourier Transform (DFT): Definition
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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.
Fourier Series and Analysis
Covers Fourier series, analysis, the heat equation, Gibbs phenomenon, and Fourier transform properties.
Discrete Fourier Transform: Unlimited Duration Signals
Explores the Discrete Fourier Transform applied to signals of unlimited duration using various windows for improved accuracy.
Discrete-Time Fourier Transform: Properties
Explores the properties of Discrete-Time Fourier Transform, including linearity, time and frequency shifts, time reversal, and convolution.
Frequency Estimation: Deterministic Signals with Low Noise Level
Explores frequency estimation in deterministic signals using the DFT and spectral resolution.
Signal Processing: Basics and Spectral Analysis
Covers the basics of signal processing, linear estimation, and digital filters.
Signal Analysis and Filter Design
Explores signal analysis, FFT, filters, and power spectral density in signal processing.
Fourier Transform and Sampling
Covers the Fourier transform of sampled signals, reconstruction, and harmonic response.
Frequency Estimation in Deterministic Case (Low Noise)
Covers frequency estimation in deterministic signals using DFT and signal processing.
Numerical Methods: Boundary Value Problems
Covers numerical methods for solving boundary value problems using Crank-Nicolson and FFT.
