Aim of the experiment

To help students develop an intuitive understanding of Wide-Sense Stationary (WSS) random processes through the visualization of their Autocorrelation functions and Power Spectral Densities (PSD). This experiment highlights the relationship between time-domain and frequency-domain representations of second-order statistics in random processes. Through this we aim that students will learn:

• Distinguish between stationary and wide-sense stationary random processes.
• Visualize the autocorrelation function as a function of time-lag (τ) in WSS processes.
• Understand the physical significance of autocorrelation in capturing second-order dependencies.
• Demonstrate how the power spectral density is obtained as the Fourier Transform of the autocorrelation function.
• Provide an interactive platform to bridge the gap between theory and visual understanding of random processes.