Linear Prediction and Estimation

Related lectures (31)

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Explores stochastic processes and the Wiener filter for signal processing.

Explores neural signal processing for brain-computer interfaces, including decoding techniques like Kalman filters and spike sorting.

Explores image restoration and signal prediction using linear filters in signal processing.

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

Covers the theory and application of the Wiener filter for discrete-time stochastic processes.

Explores harmonic signals, spectrum estimation, and signal analysis methods using MATLAB tools.

Introduces the Kalman Filter, a method to estimate system state from noisy measurements.

Delves into correlation and spectral density of signals, explaining their significance and applications.

Covers continuous-time stochastic processes in linear systems, including signal analysis and filtering.

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