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Signals & Systems I: Micro-Systems and Communication Systems
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Related lectures (31)
Signals and Systems: Sampling Theorem and Applications
Discusses the sampling theorem and its applications in signal processing.
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Explores signals, instruments, and systems, covering ADC, Fourier Transform, sampling, signal reconstruction, aliasing, and anti-alias filters.
Signals & Systems I: Introduction to Communication Systems
Covers the basics of signals and systems in communication, including modulation, medical imaging, Fourier analysis, and biological systems.
Sampling: DT-time processing of CT signals
Covers the importance of sampling in signal processing, including the sampling theorem and signal reconstruction.
Signal Processing: Sampling and Reconstruction
Covers Fourier transform, sampling, reconstruction, Nyquist frequency, and ideal signal reconstruction.
Fourier Transform and Sampling
Covers the Fourier transform of sampled signals, reconstruction, and harmonic response.
Signal Processing: Sampling and Reconstruction
Covers the concepts of quantization, coding, and sampling in signal processing.
Fourier Transform: Concepts and Applications
Covers the Fourier transform, its properties, applications in signal processing, and differential equations, emphasizing the concept of derivatives becoming multiplications in the frequency domain.
Signal Modulation and Sampling
Covers signal modulation, sampling, and their applications in communication systems.
Sampling and Reconstruction
Covers sampling, Fourier Transform, and reconstruction using low-pass filters in signal processing.
Signals & Systems I: Sampling and Reconstruction
Explores ideal sampling, Fourier transformation, spectral repetition, and analog signal reconstruction.
Sampling and Reconstruction Theory
Covers the concepts of analog, discrete, and digital signals, sampling times, frequencies, and pulses.
Signal Processing: Basics and Applications
Covers the basics of signal processing, including Fourier transform, linear systems, and signal manipulation.
Signal Processing Fundamentals
Covers the basics of signal processing and electric circuits.
Principles of Digital Communication
Covers the principles of digital communication, focusing on the Nyquist Sampling Theorem and signal space dimension.
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.
Wireless Receivers: Time and Phase Offset
Covers the impact and compensation of time and phase offset in wireless receivers.
Introduction to Sampling
Covers the concept of sampling, the sampling theorem, signal reconstruction, and the conversion of analogue signals to digital signals.
Fourier Transform: Basics and Applications
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