Data Structures and Algorithms


Kalman Folding 4: Streams and Observables

Authors: Brian Beckman

In Kalman Folding, Part 1, we present basic, static Kalman filtering as a functional fold, highlighting the unique advantages of this form for deploying test-hardened code verbatim in harsh, mission-critical environments. In that paper, all examples folded over arrays in memory for convenience and repeatability. That is an example of developing filters in a friendly environment. Here, we prototype a couple of less friendly environments and demonstrate exactly the same Kalman accumulator function at work. These less friendly environments are - lazy streams, where new observations are computed on demand but never fully realized in memory, thus not available for inspection in a debugger - asynchronous observables, where new observations are delivered at arbitrary times from an external source, thus not available for replay once consumed by the filter

Comments: 11 Pages.

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Submission history

[v1] 2016-07-10 15:52:42

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