Averaging panel – Measurement Computing eZ-Record rev.2.1 User Manual
Page 14

14
eZ-Record Manual
January 2001
The pre-trigger mode includes data before the trigger event. When you specify a
pre-trigger, data in the memory buffer that precedes the trigger event is included
in the frame of captured data. The amount of data included is based on a percent
of the frame size.
A post trigger skips data immediately after the trigger event before it starts
capturing data. The amount of skipped data is based on a percent of the frame
size. This is specified in the Delay text field.
Free Run: Data acquisition and processing begin as soon as the Acquire
button is clicked.
Input Channel: Data acquisition and processing begin after the signal on the
specified channel reaches the defined trigger conditions.
Channel: This is the channel number where the analyzer will “look for” the
trigger signal.
Pre/Post Trigger: This is the amount of data, as a percent of the frame size,
that is captured before a trigger event (pre-trigger mode) or that is skipped
after a trigger event (post-trigger).
Neg/Pos: This is the (negative/decreasing or positive/increasing) slope of the
signal that defines a trigger condition. The signal must be on the defined
slope before it is considered a candidate for a trigger.
Trigger Level: This is as a percent of the Full Scale Voltage of the trigger
channel. The signal must pass through this level before it is considered a
candidate for a trigger. The slope of the signal must also meet defined trigger
slope condition before it is recognized as a trigger or trigger event.
Analyzer Tab - Averaging Panel
This is the type of averaging that will be calculated during data acquisition.
Averaging is one technique used to decrease the noise in a measurement.
Linear: All blocks of data are treated equally in terms of their effect on the
averaged result.
Exponential: Similar to linear averaging, Exponential requires a weighting factor
that either increases or decreases the effect of each new data block on the
resultant average.
Average Weight Factor: The Weighting Factor either increases or decreases
the effect of each new data block on the resultant average when
Exponential Averaging is used.
New Average = ((New Data) * A.W.F.) + (Old Average * (1-A.W.F))
Peak Hold: The resultant block of data is a collection of points that represent
the peak amplitude for each point in the block. With each new block of data,
the current data is compared with the new data on a point by point basis.
The highest amplitude for each point in the block is retained.