Disguising a Reference So Others Can Test Your Filter

But 'reduce noise' isn't something a filter does. It separates a known type of signal from a signal + distortion + noise input, and ONLY if the signal is known in character can the filter function be evaluated.

Reducing noise/signal ratio usually results in the as-filtered data having less degrees of freedom than the initial data, i.e. it reduces a hundred points (one hundred nearly-independent numbers) to three numbers. There's potentially only

The formulation of your question is a little less than complete and coherent. But you might get an answer by clarifying your terms and purpose.

What do you mean by "reference"?

How does the "reference" relate to testing a filter?

What parameters do you wish to demonstrate?

What information are you trying to obscure?

Dale B. Dalrymple

(snip)

As I replied to Jerry's post, see the wikipedia page Trusted_client.

The problem of distributing software source, such that the recipient can use it but not modify or reverse engineer it comes up often, but there is no easy answer. (More often for HDL (hardware description language) code, but it is the same problem.

-- glen

Any one in particular you have in mind?

The usual way to do these things is to publish a method of design in one of the journals. That way the algorithm to design the filter is reviewed by people who ought to know the subject at hand.

What use would the filter be, then? It doesn't work unless you know the exact noise that corrupts the signal? It's a ridiculous idea.

Rune

That's not a question. Is English your native language?

But, why would you want it to not be directly identifiable?

Is this a one dimensional signal or an image? I bet that I can detect such an image "reference" noise by visual inspection with the "signal" noise.

Wrong.

Y1 =3D X + E

Y2 =3D C*E

where C is unknown scalar, X =3D uncorrupted signal matrix, E =3D noise matrix

Solve:

min || Y1 + A*Y2 || A

A =3D -1/C

E =3D -A*Y2

X =3D Y1 + A*Y2

Just get any ol' sound source, like a recording of "The 1812 Overture," and sum it with some pseudorandom noise, such that either could be recovered with a correlator of some kind?

Good Luck! Rich

Brett has a lot of these.

Hey, at least he's thinking!

Cheers! Rich