Vector Representation of Signals

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Related lectures (31)

Fourier Transforms: Properties and Applications

Explores Fourier transforms, including properties, convolution, Parseval's theorem, and energy spectral density for non-periodic functions.

Properties of Fourier Transform

Explores the properties and applications of the Fourier transform in signal processing and mathematics.

Orthogonal/Orthonormal Bases and Polynomials

Explores orthogonal and orthonormal bases, Gram-Schmidt process, and orthogonal polynomials in physics.

Fourier Transforms: Dirac Delta, Fourier Integral, and Transform

Explores the Dirac delta, Fourier integral, and Fourier transform applications in solving PDE problems.

Fourier Series: Approximation and Transformations

Covers the concept of Fourier series and their practical applications in signal processing.

Convolution: Effect of Main Lobe

Explains the effect of convolving any spectrum by the Fourier transform of a rectangular window.

Fourier Series: Sinusoidal Functions and Coefficients

Explains the Fourier series representation of periodic functions using sinusoidal functions and coefficients.

Signal Processing: Basics and Applications

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

Fundamental Notions - I

Explores fundamental notions in image and video processing, covering applications and key concepts like color quantization and 2D Fourier Transform properties.

Signals & Systems II: Fourier Transform Properties

Explores the properties of the Discrete-Time Fourier Transform in signal processing.

Spectrogram Analysis: Psychoacoustic Foundations & Signal Processing

Explores spectrogram analysis, including DFT, STFT, and CQT, for tasks like music transcription and onset detection.

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