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Signals, Instruments, and Systems
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Related lectures (30)
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Sampling: DT-time processing of CT signals
Covers the importance of sampling in signal processing, including the sampling theorem and signal reconstruction.
Sampling: Signal Reconstruction and Aliasing
Covers the importance of sampling, signal reconstruction, and aliasing in digital representation.
Sampling and Reconstruction
Covers sampling, Fourier Transform, and reconstruction using low-pass filters in signal processing.
Fourier Transform and Sampling
Covers the Fourier transform of sampled signals, reconstruction, and harmonic response.
The Sampling Theorem
Covers the sampling theorem, impulse train sampling, bandlimited signals, and the Nyquist rate.
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.
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.
Discrete Fourier Transform: Sampling and Interpretation
Explores discrete Fourier transform, signal reconstruction, sampling interpretation, and periodic signal repetition.
Signals and Systems: Sampling Theorem and Applications
Discusses the sampling theorem and its applications in signal processing.
