High Performance Signal Processing Tools with Fluctuation-Enhanced Sensing

We propose a high performance library of signal processing tools that incorporate a newly developed technique known as fluctuation enhanced sensing (FES) to enhance the novel microsensor developed at NIST. Our goal is to improve the performance of the NIST sensor from two angles. One is to apply our existing proven algorithms to the NIST data. The other one is to incorporate advanced FES concept to the tools. Besides the mean (steady state) sensor values collected at various temperatures, the key concept of FES is to use a low noise amplifier to enlarge the small stochastic fluctuations in the sensor. Features such as mean-square fluctuations, skewness, kurtosis, power spectrum, zero-crossing patterns, bispectrum images of the fluctuations will be extracted. The fluctuation signals contain rich characteristics about how the chemical agents are interacting with the sensors. Recently we have demonstrated that FES can significantly improve the sensitivity and selectivity of sensors.