Lectures related to Signal Processing Fundamentals

Time Series: Fundamentals and Models

Explores the fundamentals of time series analysis, including stationarity, linear processes, forecasting, and practical aspects.

Time Series: Linear Filtering and Spectral Estimation

Explores linear filtering, spectral estimation, and second-order stationarity in time series analysis.

Stochastic Processes: Basics & Stationarity

Covers signal generation, statistical relations, stationarity, white noise, and orthogonality in stochastic processes.

Dependence and Correlation

Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.

Quantifying Statistical Dependence: Covariance and Correlation

Explores covariance, correlation, and mutual information in quantifying statistical dependence between random variables.

Causal Systems & Transforms: Delay Operator Interpretation Log in to Mediaspace to watch this video

Covers z Variable as a Delay Operator, realizable systems, probability theory, stochastic processes, and Hilbert Spaces.

Parametric Signal Models: Matlab Practice Log in to Mediaspace to watch this video

Covers parametric signal models and practical Matlab applications for Markov chains and AutoRegressive processes.

Linear Estimation & Prediction: Models & Methods Log in to Mediaspace to watch this video

Explores linear estimation and prediction in AR parametric models, focusing on Yule Walker equations and Wiener filter.

Statistical Signal Processing Tools Log in to Mediaspace to watch this video

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

Yule Walker Equations: Efficient Implementation and Correlation Analysis Log in to Mediaspace to watch this video

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

Probability and Stochastic Processes: Fundamentals and Applications Log in to Mediaspace to watch this video

Discusses the fundamentals of probability and stochastic processes, focusing on random variables, their properties, and applications in statistical signal processing.

Properties of Time-Frequency Domain Signals Log in to Mediaspace to watch this video

Covers the main properties of time-frequency domain signals and their limitations.

Parseval Relations and Fourier Transform Log in to Mediaspace to watch this video

Covers Parseval relations, Fourier series, energy calculation, and correlation in signal processing.

Air Pollution: Correlation Analysis Log in to Mediaspace to watch this video

Covers correlation and cross-correlations in air pollution data analysis, including time series, autocorrelations, Fourier analysis, and power spectrum.

Elements of Statistics: Estimation & Distributions Log in to Mediaspace to watch this video

Covers fundamental statistics concepts, including estimation theory, distributions, and the law of large numbers, with practical examples.

Frequency Estimation (Theory)Log in to Mediaspace to watch this video

Covers the theory of numerical methods for frequency estimation on deterministic signals, including Fourier series and transform, Discrete Fourier transform, and the Sampling theorem.

Central Limit Theorem: Properties and Applications Log in to Mediaspace to watch this video

Explores the Central Limit Theorem, covariance, correlation, joint random variables, quantiles, and the law of large numbers.

Signal Approximation and Orthogonal Bases Log in to Mediaspace to watch this video

Explores signal approximation, orthogonal bases, Fourier series, correlation, and vector geometry.

Signals and Systems I: Fourier Transform and Spectral Analysis Log in to Mediaspace to watch this video

Explores Fourier series, energy calculation, functional spaces, correlation spectra, and spectral density in signals and systems.

Harmonic Signals and Spectrum Estimation Log in to Mediaspace to watch this video

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