Lectures related to Signals & Systems II: Stationary Signals and Spectral Density

Signal Processing Fundamentals

Explores signal processing fundamentals, including discrete time signals, spectral factorization, and stochastic processes.

Stochastic Models for Communications: Continuous-Time Linear Systems

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

Harmonic Signals and Spectrum Estimation

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

Linear Prediction and Estimation

Explores linear prediction, optimal filters, random signals, stationarity, autocorrelation, power spectral density, and Fourier transform in signal processing.

Statistical Signal Processing Tools

Explores statistical signal processing tools for wireless communications, including spectral estimation and signal detection, classification, and adaptive filtering.

Linear Estimation and Prediction: Part 2

Covers the estimation and prediction of random signals in linear systems.

Continuous-Time Stochastic Processes: Spectral Density

Covers the spectral density of continuous-time stochastic processes and its estimation.

Stochastic Processes: Power Spectral Density

Explores power spectral density in continuous-time stochastic processes and its significance in signal processing applications.

Spectral Estimation Methods

Explores parametric spectrum estimation methods, including line and smooth spectra, and delves into heart rate variability analysis.

Power Spectral Density Computation

Covers the computation of power spectral density and the design of communication systems.

Signal Processing: Correlation and Spectral Density

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

Yule Walker Equations: Efficient Implementation and Correlation Analysis

Explores Yule Walker equations for efficient implementation and correlation analysis in signal processing.

Statistical Signal & Data Processing

Explores Statistical Signal & Data Processing fundamentals, tools, and applications in various fields.

Estimation and Linear Prediction - Part 2

Explores power spectral density, Wiener-Khintchine theorem, ergodicity, and correlation estimation in random signals for signal processing.

Spectral Analysis: Integrated Spectrum and Autocovariance

Explores spectral analysis, integrated spectrum, autocovariance, estimation, and convergence in time series models.

Sphere Packing

Covers the concept of sphere packing and its significance in time shifts and Nyquist criterion.

Statistical Signal Processing for Wireless Communications

Covers statistical signal processing tools for wireless communications, including spread spectrum, spectral analysis, ultra-wide band communications, and heart rate variability analysis.

Stochastic Processes for Communications: Continuous-Time Stationarity

Covers the concept of stationarity in continuous-time stochastic processes and its applications in communication systems.

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.

Time Series: Stochastic Properties and Modelling

Explores the stochastic properties and modelling of time series, covering autocovariance, stationarity, spectral density, estimation, forecasting, ARCH models, and multivariate modelling.