SUMMARY
The discussion focuses on the properties of white Gaussian noise (WGN) processes, specifically the expected value of the product of samples from the process. It establishes that for a complex white noise process, E[w[n1] w*[n2]] equals 0, similar to the case for real white noise where E[w[n1] w[n2]] also equals 0. The key conclusion is that the ensemble average of the auto-correlation function for WGN is zero, regardless of whether the process is real or complex.
PREREQUISITES
- Understanding of white Gaussian noise (WGN) processes
- Knowledge of expected value and auto-correlation functions
- Familiarity with complex random processes
- Basic concepts of signal processing
NEXT STEPS
- Study the properties of complex random processes in signal processing
- Learn about the implications of auto-correlation functions in WGN
- Explore the concept of ensemble averages in stochastic processes
- Investigate the effects of time-reversal on signal properties
USEFUL FOR
Signal processing engineers, researchers in stochastic processes, and students studying random processes will benefit from this discussion.
