Binning And Measurement Accuracy - LeCroy WaveMaster 8600A Operator's Manual

X-Stream Operator's Manual
Determining such peaks is very useful because they indicate dominant values of a signal. However,
signal noise and the use of a high number of bins relative to the number of parameter values
acquired, can give a jagged and spiky histogram, making meaningful peaks hard to distinguish. The
scope analyzes histogram data to identify peaks from background noise and histogram definition
artifacts such as small gaps, which are due to very narrow bins.

Binning and Measurement Accuracy

Histogram bins represent a sub-range of waveform parameter values, or events. The events
represented by a bin may have a value anywhere within its sub-range. However, parameter
measurements of the histogram itself, such as average, assume that all events in a bin have a
single value. The scope uses the center value of each bin's sub-range in all its calculations. The
greater the number of bins used to subdivide a histogram's range, the less the potential deviation
between actual event values and those values assumed in histogram parameter calculations.
Nevertheless, using more bins may require that you perform a greater number of waveform
parameter measurements, in order to populate the bins sufficiently for the identification of a
characteristic histogram distribution.
In addition, very fine grained binning will result in gaps between populated bins that may make it
difficult to determine peaks.
The oscilloscope's 20,000-parameter buffer is very effective for determining the optimal number of
bins to be used. An optimal bin number is one where the change in parameter values is insignificant,
and the histogram distribution does not have a jagged appearance. With this buffer, a histogram
can be dynamically redisplayed as the number of bins is modified by the user. In addition,
depending on the number of bins selected, the change in waveform parameter values can be seen.
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