>there is nothing *motivating* us to define Rx[k] = E{x[n] x[n+k]} except
that we
>expect that expectation value (which is an average) to be the same as the
other definition
Sure there is. That definition gets you everything you need to work out a
whole list of major results (for example, optimal
>no. we need ergodicity to take a definition of autocorrelation, which we
are all familiar with:
> Rx[k] = lim_{N->inf} 1/(2N+1) sum_{n=-N}^{+N} x[n] x[n+k]
>and turn that into a probabilistic expression
> Rx[k] = E{ x[n] x[n-k] }
>which we can figger out with the joint p.d.f.
That's one
Original Message
Subject: Re: [music-dsp] confirm 2692e89dd013da35bd113d6f644fdcfa865054c3
From: "Douglas Repetto"
Date: Thu, November 12, 2015 10:26 am
To: "A discussion list for music-related DSP"
Original Message
Subject: Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?
From: "Ethan Duni"
Date: Wed, November 11, 2015 7:36 pm
To: "robert bristow-johnson"
Original Message
Subject: Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?
From: "Ethan Duni"
Date: Wed, November 11, 2015 5:57 pm
To: "robert bristow-johnson"
>all ergodic processes are stationary. (not necessarily the other way
around.)
Ah, right, there is no constant mean for a time average to converge to if
the process isn't stationary in the first place. Been a while since I
worried about the details of ergodicity, mostly I have the intuitive