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Lesson 1 - Key Challenges that Impact IoT Product Reliability
In this course we'll cover the theory and application of our waveform analytics software, which uses AI techniques to capture and rapidly identify anomalous waveforms within massive databases. Using our CX3300 Device Current Analyzer, the waveform analytics software allows you to capture long streams of waveforms (10 MSa/s for up to 100 hours) in both voltage and current. The software uses unsupervised machine learning techniques to tag waveforms in real time as it takes data, enabling you to quickly locate waveform anomalies (even in databases with over one million waveforms) immediately after the data capture completes.
Who should take Using Anomalous Waveform Analytics for IoT Device Analysis?
Engineers responsible for the reliability of IoT devices and who need an efficient means to identify rare anomalies that occur during long-duration device operation would benefit from taking this course. Since this software is very general purpose, engineers concerned with IoT battery life can also use it to verify power consumption.
- Key Challenges that Impact IoT Product Reliability
- Keysight Solutions - CX3300A and Anomalous Waveform Analytics
- Efficient Analysis of Large Data Sets
- Demo: Anomalous Waveform Analytics
- Application Examples of Anomalous Waveform Analytics