Informatics and Machine Learning

12Stochastic Sequential Analysis (SSA)

A protocol has been developed for the discovery, characterization, and classification of localizable, approximately stationary, statistical signal structures in stochastic sequential data, such as the channel current data to be described in Chapter 14.

The stochastic sequential analysis (SSA) methods described in what follows, provide a robust and efficient means to make a device or process “smart” (e.g., a “smartening” is possible with a software AI effecting the operational role of a Maxwell Demon on the flow of information, instead of the classic example of flow of hot/cold matter in a preferential manner), with possible enhancement to device (or process) sensitivity and productivity and efficiency, as well as possibly enabling new capabilities for the device or process (via transduction coupling, for example, as with the nanopore transduction detector [NTD] platform in Chapter 14). The SSA Protocol can work with existing device or process information flows, or can work with additional information induced via modulation or introduction via transduction couplings (comprising carrier references [90, 91], among other things, see Chapter 14). Hardware device‐smartening may be possible via introduction of modulations or transduction couplings, when used in conjunction with the SSA Protocol implemented to operate on the appropriate timescales to enable real‐time experimental or operational control, where real‐time adaptive pattern recognition ...