Fundamental Notions - I

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Related lectures (31)

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Fourier Transform and Sampling

Covers the Fourier transform of sampled signals, reconstruction, and harmonic response.

Discrete Fourier Transform: Sampling and Interpretation

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

Psychoacoustics and Signal Processing

Explores psychoacoustics, signal processing, and the brain's interpretation of sound frequencies, covering topics like the Missing Fundamental phenomenon and the inner workings of the cochlea.

Sampling and Reconstruction Theory

Covers the concepts of analog, discrete, and digital signals, sampling times, frequencies, and pulses.

Signal Representations

Covers the properties of signal/data representations using Fourier transformations and matrices.

Signal Processing: Basics and Applications

Covers the basics of signal processing, including Fourier transform, linear systems, and signal manipulation.

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.

Image Processing II: DFT, DCT, and Wavelet Transforms

Explores eigenfaces, DFT, DCT, and wavelet transforms in image processing.

Signal Processing: Basics and Spectral Analysis

Covers the basics of signal processing, linear estimation, and digital filters.

Fourier Transform: Basics and Examples

Explains the basics of Fourier transform and demonstrates its application through examples, including periodic functions and Fourier Transform Pairs.