Audyssey odessey

[E-Stat]

And that sum would be a flat or close to flat frequency curve at each seat, just like my words stated.

At one seat, perhaps. At another, not exactly given the averaging of all the individual points. Averaging multiple answers gives you good answers for all, but one most certainly CANNOT say that it only affects certain areas of the room. Such is impossible using seven speakers.

Ralph, you can see on the screen of your television set what equalization calculation that each measured position gets.

More specifically, the correction factor for each position. Which never is found at the output of the device. Instead, each is combined with all the others to provide a lump sum product. One answer for all positions. Ten positions. A thousand positions. Doesn't matter. You've only got one output! That is all that matters because the output signal never sends any one individual position's EQ. One speaker is incapable of sending ten unique signals as you continue to assert.

You keep quoting how MultiEQ pro works, but you have yet to make one point about MultiEQ XT32 pro works. Multi EQ XT32 pro has more filters, with more resolution, more horsepower which leads to the ability to provide finer calculations for those many more points.

And still results in a single correction applied via a single speaker to each and every position in the room. Smarter and better weighting factors for sure. In the end, one solution. The only possible way to deliver position specific EQ is to provide position specific speakers! Comprende, senior?

Unlike MultiEQ pro, it does not work in clusters, it works on individual positions. If position A falls into the target curve, it does not re-equalize that position.

That provides a more accurate weighting factor which gets summed with all the other weighting factors. There remains, however, only one averaged output. There is only one summarized solution for the room.

While the application is different, I write software that uses various weighting factors to determine supply chain demand. Using standard deviation, you eliminate outlier values. You employ time based exponential smoothing to weight demand based upon multiple factors. You build in as much intelligence as you can to provide the best single result. Unquestionably, intelligently weighted systems work better than those using simple arithmetic averaging. They CANNOT, however, under any circumstance provide separate simultaneous solutions for different scenarios.

rw