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Lecture
Sampling and Reconstruction
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Related lectures (30)
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Sampling and Reconstruction Theory
Covers the concepts of analog, discrete, and digital signals, sampling times, frequencies, and pulses.
Signals, Instruments, and Systems
Explores signals, instruments, and systems, covering ADC, Fourier Transform, sampling, signal reconstruction, aliasing, and anti-alias filters.
Signal Processing Fundamentals
Covers the basics of signal processing and electric circuits.
Signals & Systems I: Sampling and Reconstruction
Explores ideal sampling, Fourier transformation, spectral repetition, and analog signal reconstruction.
Signal Processing: Sampling and Reconstruction
Covers Fourier transform, sampling, reconstruction, Nyquist frequency, and ideal signal reconstruction.
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.
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.
Signals and Systems: Sampling Theorem and Applications
Discusses the sampling theorem and its applications in signal processing.
Smart Sensors for the IoT: ADCs Fundamentals
Explores ADCs fundamentals for IoT smart sensors, covering quantization, non-idealities, and topologies.
