PathWave Waveform Analytics

Debug voltage and current spikes, IO glitches, and time shifts in pre-silicon using powerful machine learning

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Designing and manufacturing low-power products that are robust, reliable, and secure requires the collection and analysis of extensive and long-duration waveform data from oscilloscopes and analyzers. Automate this extremely manual task and raise your engineering productivity without sacrificing accuracy.

Keysight's PathWave Waveform Analytics is an edge-to-cloud computing application that enables long-duration waveform compression, high-resolution playback, and multi-terabyte data analysis.

The automated technology combines pre- and post-processing machine learning models that streamline anomaly discovery. The software helps you find waveform anomalies quickly and accurately.

  • Compress long-duration waveforms by 60%
  • Reduce waveform transfer time by 10x
  • Easily transfer data using edge-to-cloud computing applications
  • Reduce storage space with high compression ratio
  • Reduce required engineering hours by 10x
  • Perform multi-level data drill-down analysis in higher resolution

Detect Anomalies Quickly Using Machine Learning

With its AI-based outlier detection and classification capabilities, PathWave Waveform Analytics enables R&D and design validation engineers to quickly detect anomalies such as voltage and current spikes on power and signal waveforms.

Performing manual inspections of large waveform data sets is no longer necessary. Instead, you can run multiple validation tests over multiple channels of an integrated circuit. You can also easily identify functional inconsistencies, rectify them quickly, and shorten your analysis time, thereby reducing your time-to-market.

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