Random signals and systems deal with unpredictable, stochastic processes that evolve over time, often modeled using probability and statistics. They are essential in communications, control, and signal processing for analyzing noise, interference, and uncertain behaviors. Key concepts include random variables, autocorrelation, power spectral density, and stationarity. Systems with random inputs are studied using techniques like Wiener and Kalman filtering for optimal estimation. Applications span radar, wireless networks, and financial modeling, where uncertainty plays a critical role.
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