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W
AVE
R
UNNER
X
I
S
ERIES
130
WRXi-OM-E Rev B
S
UMMED
A
VERAGING
Summed Averaging is the repeated addition, with equal weight, of successive source waveform records. If a
stable trigger is available, the resulting average has a random noise component lower than that of a single-shot
record. Whenever the maximum number of sweeps is reached, the averaging process stops.
An even larger number of records can be accumulated simply by changing the number in the dialog. However, the
other parameters must be left unchanged or a new averaging calculation will be started. You can pause the
averaging by changing the trigger mode from NORM/AUTO to STOP. The instrument resumes averaging when
you change the trigger mode back to NORM/AUTO.
You can reset the accumulated average by pushing the CLEAR SWEEPS button or by changing an acquisition
parameter such as input gain, offset, coupling, trigger condition, timebase, or bandwidth limit. The number of
current averaged waveforms of the function, or its zoom, is shown in the acquisition status dialog. When summed
averaging is performed, the display is updated at a reduced rate to increase the averaging speed (points and
events per second).
C
ONTINUOUS
A
VERAGING
Continuous Averaging, the default setting, is the repeated addition, with unequal weight, of successive source
waveforms. It is particularly useful for reducing noise on signals that drift very slowly in time or amplitude. The
most recently acquired waveform has more weight than all the previously acquired ones: the continuous average
is dominated by the statistical fluctuations of the most recently acquired waveform. The weight of ‘old’ waveforms
in the continuous average gradually tends to zero (following an exponential rule) at a rate that decreases as the
weight increases.
The formula for continuous averaging is
new average = (new data + weight * old average)/( 1)
This is also the formula used to compute summed averaging. But by setting a
sweeps
value, you establish a fixed
weight that is assigned to the old average once the number of
sweeps
is reached.
For example, for a sweeps (weight) value of
4
:
1
st
sweep (no old average yet):
new average = (new data +0 * old average)/(0 + 1) = new data only
2
nd
sweep:
new average = (new data + 1*old average)/(1 + 1) = 1/2 new data +1/2 old average
3
rd
sweep:
new average = (new data + 2 * old average)/(2 + 1) = 1/3 new data + 2/3 old average
4
th
sweep:
new average = (new data + 3 * old average)/(3 + 1) = 1/4 new data + 3/4 old average
5
th
sweep:
new average = (new data + 4 * old average)/(4 + 1) = 1/5 new data + 4/5 old average
6
th
sweep:
new average = (new data + 4 * old average)/(4 + 1) = 1/5 new data + 4/5 old average
7
th
sweep:
new average = (new data + 4 * old average)/(4 + 1) = 1/5 new data + 4/5 old average
In this way, for sweeps > 4 the importance of the old average begins to decrease exponentially.
Note:
The number of sweeps used to compute the average will be displayed in the bottom line of the trace
descriptor label: