Introduction to Sampling

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Fourier Transform

Covers the Fourier Transform, properties, periodic signals, and digital signals.

Digital Signal Processing: Theory

Covers the theory of digital signal processing, including sampling, transformation methods, digitization, and PID controllers.

Signal Sampling

Explores representing analog signals digitally through sampling and quantization, discussing sampling frequency, undersampling consequences, and the stroboscopic effect.

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.

Sampling of Signals 6: Sampling a Pure Sinusoid

Explores the sampling of pure sinusoids, emphasizing the Nyquist theorem and its practical implications.

Signal Modulation and Sampling

Covers signal modulation, sampling, and their applications in communication systems.

Discrete Fourier Transform: Sampling and Interpretation

Explores discrete Fourier transform, signal reconstruction, sampling interpretation, and periodic signal repetition.

Fourier Transform: Basics and Applications

Covers the basics of the Fourier transform and its applications in signal processing.

Discrete Fourier Transform: Introduction and Sampling

Covers the introduction of discrete Fourier transform and its implications on signal reconstruction.

Numerical Control of Dynamic Systems

Covers topics like digital filtering, stability, and discrete systems, including experiments and manipulations.