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Learn random processes through intuitive explanations of mathematical models, their properties, and applications in parameter estimation for noisy measurements, covering fundamental concepts including Poisson processes, stationary random processes, autocorrelation, power spectral density (PSD), wide sense stationary (WSS) processes, and ergodicity, with practical examples from digital communications to understand how these theoretical concepts apply to real-world signal processing scenarios.
