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Signal Processing: Block Average | Spectrum

The Block Average Module improves the fidelity of noisy repetitive signals. Multiple repetitive acquisitions with very small dead-time are accumulated and averaged. Random noise is reduced
by the averaging process improving the visibility of the repetitive signal.

Features

  • Structural block Diagram of block average modeSignal Averaging in Hardware
  • Maximum waveform length of 128 kSamples (one channel)
  • Maximum average waveform throughput of more than 5,000,000 waveforms per second
  • All channels are averaged
  • Fully compatible with synchronization
  • Low dead time between waveforms: 80 ns at 500 MS/s or 64 ns at 5 GS/s
  • Fully compatible with Spectrum API which allows usage with C/C++, Delphi, Basic, LabVIEW, MATLAB and many more
  • Fully integrated into SBench 6 Professional software
  • Available for all high-speed digitizers based on M4i technology
  • Fast data calculation in hardware reduces the needed transfer bandwidth extremely
  • Calculation can run on all channels simultaneously

The complete averaging process is done inside the FPGA of the digitizer generating no CPU load at all. The amount of data is greatly decreased as well as the needed transfer bandwidth is heavily reduced. The signal processing firmware also includes the standard firmware that allows normal digitizer operation with no limitations.

Example

Noisy time signal with average improvements

The right side screenshot shows the improvement of a signal that is completely overlayed by a random noise when using different averaging factors.

While the source signal is not even visible in the original single-shot signal a 10 times average of the signal already shows that there is a signal with 5 peaks. Doing a block average of 1000 times improves the signal quality extremely showing us the real shape of the signal including all secondary maximum and minimum peaks.

The example was taken with 500 MS/s (2 ns)  timescale and 14 bit ADC resolution having a signal level of about 2 mV.

Please click the picture to enlarge it.

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