Signals & Systems II: Complex Random Vectors and Stationarity

Related lectures (31)

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Explores Gaussian vectors, moment generating functions, independence, density functions, affine transformations, and quadratic forms.

Covers the proof of the recursive formula for the optimal gains in LQ control over a finite horizon.

Explores memorylessness in distributions, stationary processes, and estimation using MLE.

Covers probability theory, distributions, and estimation in statistics, emphasizing accuracy, precision, and resolution of measurements.

Covers the joint equidistribution of CM points in algebraic structures and quadratic forms.

Explores pseudo-Euclidean spaces, emphasizing isometries and bases in vector spaces with non-degenerate quadratic forms.

Delves into Oppenheim's conjecture on quadratic forms and their connection to number theory.

Explores symmetric matrices, quadratic forms, and critical points in functions of two variables.

Covers stochastic models for communications, including stationarity, ergodicity, power spectral density, and Wiener filter.

Covers non-negative definite matrices, covariance matrices, and Principal Component Analysis for optimal dimension reduction.