Stochastic Models for Communications: Continuous-Time Stochastic Processes

Related lectures (31)

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Covers the properties of Linear Time-Invariant (LTI) systems and their implications.

Explores system analysis in the time domain, covering mathematical modeling, transfer functions, responses, and system identification.

Explores distributions, linear systems, impulse response, convolution operators, and causal systems in signals and systems.

Discusses oscillations, energy transfer, and the Green function in physics.

Explores the frequency response of stable LTI systems in both continuous-time and discrete-time domains.

Covers the analysis of LTI systems using impulse response and convolution.

Covers distributions, linear systems, impulse response, convolution, and examples of linear systems.

Explores stability and solutions of linear systems in continuous and discrete time.

Covers spectral densities, signal correlations, and white noise processes in stochastic systems.

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