Concept
Spectral density estimation
Related lectures (174)
Frequency Estimation: Deterministic Signals with Low Noise Level
Explores frequency estimation in deterministic signals using the DFT and spectral resolution.
Time Series: Representation and Modelling
Covers the stochastic properties of time series, stationarity, autocovariance, special stochastic processes, spectral density, digital filters, estimation techniques, model checking, forecasting, and advanced models.
Statistical Signal Processing Tools
Explores statistical signal processing tools for wireless communications, including spectral estimation and frequency modeling.
Signal Analysis and Filter Design
Explores signal analysis, FFT, filters, and power spectral density in signal processing.
Fast Fourier Transform (FFT): Lecture 4
Covers the Fast Fourier Transform (FFT) algorithm, interpolation, filters, image processing, and experimental techniques in TEM and STM.
Frequency estimation for stochastic signals (large noise)
Covers numerical experiments for frequency estimation of stochastic signals.
Wireless Receivers: Parameter Estimation
Covers the challenges and techniques of parameter estimation in wireless receivers.
Statistical Signal Processing for Wireless Communications
Introduces statistical signal processing tools for wireless communications, emphasizing practical applications and hands-on experience with Python or Matlab.
Poincare Inequality: Young the Quality on the Night
Covers mathematical estimations and algebraic identities in fully discrete problems.
Stochastic Models for Communications
Covers stochastic models for communications, including stationarity, ergodicity, power spectral density, and Wiener filter.