Random Signal Processing

Random signal processing involves analyzing and interpreting signals that vary unpredictably over time, such as noise, stock prices, or natural phenomena. Instead of deterministic patterns, these signals are characterized by probabilities and statistical properties. Techniques in this field help engineers and scientists filter noise, detect meaningful information, or predict future behavior. By understanding the statistical behavior of such signals, we can design systems that efficiently extract useful data from unpredictable environments, leading to applications in communications, radar, audio processing, and more.