Study the statistical properties of the output response of a system when the input is wide sense stationary
1. In the context of a wide-sense stationary (WSS) process, which of the following is true regarding the concept of **ergodicity**?
2. An LTI system has an impulse response that is zero for all values of time greater than a certain constant. What does this imply about the system?
3. In the context of discrete-time systems, what is the implication of having poles outside the unit circle in the z-domain for the system's stability and behavior?
4. How does the inclusion of a moving average (MA) term in an ARMA model affect its frequency response?
5. In the context of stochastic processes, what distinguishes a strict-sense stationary (SSS) process from a wide-sense stationary (WSS) process in terms of their moment invariance properties?
6. When a wide-sense stationary (WSS) signal passes through a Linear Time-Invariant (LTI) system, what impact does the system's characteristics have on the stationarity and statistical properties of the output signal?
7. In an ARMA(1,1) model, what happens when the pole and zero are very close to each other in the z-domain?
8. For an AR(2) process defined by X(n) = a1·X(n−1) + a2·X(n−2) + W(n), where W(n) is white noise, what does it imply about the spectral characteristics of the process if the characteristic equation has roots lying exactly on the unit circle in the z-plane?
9. How does the inclusion of a high-order AR term in an ARMA model influence its autocorrelation properties?
10. What is the effect of adding a long-memory MA term to an ARMA model in the frequency domain?