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We often need to process signals that are produced by devices fabricated within our group or systems that are put together by our team members. The signal processing methods that we employ range from mechanical designs to analog interfaces to large scale, multi-sensor signal processing. In doing so, we take advantage of our knowledge of device physics to embedded programming and machine learning.

Examples of signal processing methods in our lab include:
  • Coupling of resonant microsensors for enhanced performance
  • Linear and nonlinear analog circuits
  • Long- and short-term statistical analysis
  • Multi-sensor and multi-source data fusion
  • Data classification and characterization