Lecture

Signals & Systems I: Vector Approximation and Signal Comparison

Description

This lecture covers topics such as least squares approximation, signal detection, correlation, complex Fourier series, orthogonal families of functions, orthogonal bases, trigonometric Fourier series, signal approximation, vector components, dot product, vector geometry, linear approximation, norm and energy of a signal, signal vector space, best approximation of signals, scalar product, and correlation and similarity measures.

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