I've been told that Ergodicity gives us a practical vision of processes WSS (Wise-sense stationary) and a bunch of integrals. For me, it is not enough to fully understand it.

Could someone explain me Ergodicity in a simple way?

EDIT:

Thank you all for those interested in the question and answered, here i will share an example:

y(t) is a random process where {i(t),q(t)} are two random stationary processes, incorrelated, null mean and autocorrelation Ri(z) = Rq(z).

y(t) = i(t)cos(2πf0t)−q(t)sin(2πf0t)

The exercise asks for mean and autocorrelation of y(t) and finally if that process is stationary or cyclostationary.

I have resolved that already but, what about ergodicity.

Is this process ergodic? How could i demonstrate such thing?

I've been told that Ergodicity gives us a practical vision of processes WSS (Wide-sense stationary) and a bunch of integrals. For me, it is not enough to fully understand it.

Could someone explain me Ergodicity in a simple way?

EDIT:

Thank you all for those interested in the question and answered, here I will share an example:

$y(t)$ is a random process where $\{i(t),q(t)\}$ are two random stationary processes, incorrelated, null mean and autocorrelation $Ri(z) = Rq(z)$.

$$y(t) = i(t)\cos(2\pi f_0t)−q(t)\sin(2\pi f_0t)$$

The exercise asks for mean and autocorrelation of y(t) and finally if that process is stationary or cyclostationary.

I have resolved that already but, what about ergodicity?

Is this process ergodic? How could I demonstrate such thing?

I've been told that Ergodicity gives us a practical vision of processes WSS (Wise-sense stationary) and a bunch of integrals. For me, it is not enough to fully understand it.

Could someone explain me Ergodicity in a simple way?

I've been told that Ergodicity gives us a practical vision of processes WSS (Wise-sense stationary) and a bunch of integrals. For me, it is not enough to fully understand it.

Could someone explain me Ergodicity in a simple way?

EDIT:

Thank you all for those interested in the question and answered, here i will share an example:

y(t) is a random process where {i(t),q(t)} are two random stationary processes, incorrelated, null mean and autocorrelation Ri(z) = Rq(z).

y(t) = i(t)cos(2πf0t)−q(t)sin(2πf0t)

The exercise asks for mean and autocorrelation of y(t) and finally if that process is stationary or cyclostationary.

I have resolved that already but, what about ergodicity.

Is this process ergodic? How could i demonstrate such thing?

Intro

I am studying Communications and i was reading about random processes. I've been told that Ergodicity gives us a practical vision of processes WSS (Wise-sense stationary) and a bunch of integrals. For me, it is not enough to fully understand it.

Could someone explain me Ergodicity in a simple way?

Thanks

I've been told that Ergodicity gives us a practical vision of processes WSS (Wise-sense stationary) and a bunch of integrals. For me, it is not enough to fully understand it.

Could someone explain me Ergodicity in a simple way?