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Lecture
Signals & Systems II: Sampling and Signal Representation
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Related lectures (31)
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Wireless Receivers: Parameter Estimation
Covers parameter estimation in wireless receivers and phase ambiguity in signal modeling.
Discrete Fourier Transform: Introduction and Sampling
Covers the introduction of discrete Fourier transform and its implications on signal reconstruction.
Sampling: Signal Reconstruction and Aliasing
Covers the importance of sampling, signal reconstruction, and aliasing in digital representation.
Signal Processing Fundamentals
Covers the basics of signal processing and electric circuits.
Signal Processing: Basic Definitions and Properties
Explores basic signal definitions, properties, and digital signal processing techniques.
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.
Canonical Representation of Discrete Signals
Explores the canonical representation of discrete signals as a linear combination of dispersed pulses and other related concepts.
Signals and Systems: Sampling Theorem and Applications
Discusses the sampling theorem and its applications in signal processing.
Discrete Fourier Transform: Introduction
Introduces the discrete Fourier transform, a key tool for digital signal analysis.
Analog and Digital Conversion
Explores analog and digital signal processing, A/D and D/A conversion, resolution, settling time, and digital interfaces in electronic circuits.
