Fourier Transform: Basics and Applications

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Explores signals, instruments, and systems, covering ADC, Fourier Transform, sampling, signal reconstruction, aliasing, and anti-alias filters.

Signal Processing: Sampling and Reconstruction

Covers the concepts of quantization, coding, and sampling in signal processing.

Fourier Transform and Sampling

Covers the Fourier transform of sampled signals, reconstruction, and harmonic response.

Sampling: DT-time processing of CT signals

Covers the importance of sampling in signal processing, including the sampling theorem and signal reconstruction.

Sampling and Reconstruction

Covers sampling, Fourier Transform, and reconstruction using low-pass filters in signal processing.

Signal Processing: Sampling and Reconstruction

Covers Fourier transform, sampling, reconstruction, Nyquist frequency, and ideal signal reconstruction.

Signal Processing: Basics and Applications

Covers the basics of signal processing, including Fourier transform, linear systems, and signal manipulation.

Signal processing and vector spaces

Emphasizes the significance of vector spaces in signal processing, offering a unified framework for various signal types and system design.

Frequency Estimation (Theory)

Covers the theory of numerical methods for frequency estimation on deterministic signals, including Fourier series and transform, Discrete Fourier transform, and the Sampling theorem.

Signal Processing Fundamentals

Covers the basics of signal processing and electric circuits.