Teledyne LeCroy WaveExpert 100H Operators Manual - Manual (Page 191)

Wave Expert
WE-OM-E Rev A
189
button.
6. Touch inside the Sweeps data entry field and type in a value using the pop-up keypad. The
valid range is 1 to 1,000,000 sweeps.
Enhanced Resolution
ERES (Enhanced Resolution) filtering increases vertical resolution, allowing you to distinguish
closely spaced voltage levels. The functioning of the instrument's ERES is similar to smoothing the
signal with a simple, moving-average filter. However, it is more efficient concerning bandwidth and
pass-band filtering. Use ERES on single-shot waveforms, or where the data record is slowly
repetitive (when you cannot use averaging). Use it to reduce noise when your signal is noticeably
noisy, but you do not need to perform noise measurements. Also use it when you perform
high-precision voltage measurements: zooming with high vertical gain, for example.
How the Instrument Enhances Resolution
The instrument's enhanced resolution feature improves vertical resolution by a fixed amount for
each filter. This real increase in resolution occurs whether or not the signal is noisy, or your signal is
single-shot or repetitive. The signal-to-noise ratio (SNR) improvement you gain is dependent on the
form of the noise in the original signal. The enhanced resolution filtering decreases the bandwidth
of the signal, filtering out some of the noise.
The instrument's constant phase FIR (Finite Impulse Response) filters provide fast computation,
excellent step response in 0.5 bit steps, and minimum bandwidth reduction for resolution
improvements of between 0.5 and 3 bits. Each step corresponds to a bandwidth reduction factor of
two, allowing easy control of the bandwidth resolution trade-off. The parameters of the six filters are
given in the following table.
Resolution
increased by
-3 dB Bandwidth
(× Nyquist)
Filter Length
(Samples)
0.5 0.5 2
1.0 0.241 5
1.5 0.121 10
2.0 0.058 24
2.5 0.029 51
3.0 0.016 117
With low-pass filters, the actual SNR increase obtained in any particular situation depends on the
power spectral density of the noise on the signal.
The improvement in SNR corresponds to the improvement in resolution if the noise in the signal is
white -- evenly distributed across the frequency spectrum.
If the noise power is biased towards high frequencies, the SNR improvement will be better than the
resolution improvement.