there is 5 averaging cases in 89600 , in the use's guide all are described .

can somebody tell me which case i should choose to use in a specifically application. Thanks a lot!

can somebody tell me which case i should choose to use in a specifically application. Thanks a lot!

Continuous Peak-Hold Averaging

RMS (Video) Averaging

RMS (Video) Exponential Averaging

Time Averaging

Time Exponential Averaging

Let's look at some theories of averaging first.

The analyzer offers several types of averages for averaged measurements. Some of these use exponential averaging. Unlike linear averaging (also called non-exponential or normal averaging), exponential averaging weights new data more than old data. This is useful for tracking data that changes over time.

With exponential averaging, the number of averages you select determines the weighting of old versus new data. As the number of averages increases, new data is weighted less.

To calculate the exponential average, the analyzer uses this formula:

[1/Nxnew]+[(n-1)/Nxold]

So far, I believe you can distinguish the exponential and linear averagingAnd then we can look at the difference between RMS and time averaging. Basically, RMS averaging is for spectrum trace and time averaging is for time domain data.Time-domain and correlation traces are not affected by rms averaging. In other words, traces that show time-domain data are NOT averaged when rms or rms exponential averaging is selected.

Time corrections are shown in the previous block diagram for completeness; however, time corrections are not required to perform time averaging.

With time averaging, the analyzer averages "N" time records (where "N" is the number of averages), and then stops. You can then use Restart to repeat the process,.

Although measurements made with time averaging have better signal-to-noise ratios than rms averaging, there are some restrictions:

For Continuous Peak-Hold Averaging, it's very like a peak hold function.Technically, continuous peak-hold averaging is not really a type of averaging, because the results are not mathematically averaged. But it's still considered a type of averaging because it combines the results of several measurements into one final measurement result.

You also can search "averaging" in 89600 Help to get more explanations.