A Brownian Motion Model and Extreme Belief Machine for Modeling Sensor Data Measurements

2017/04/01 by Robert A. Murphy, Murphy, Robert A.
Computer Science · Engineering · #60J70 #FOS: Computer and information sciences #Fault Detection and Control Systems #Machine Learning and ELM #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE) #cs.NE #msc:60J70

paper · pdf · doi:10.48550/arxiv.1704.00207

openalex publication_date 2017/04/01 · arxiv created 2017/04/04 · arxiv updated 2017/04/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

As the title suggests, we will describe (and justify through the presentation of some of the relevant mathematics) prediction methodologies for sensor measurements. This exposition will mainly be concerned with the mathematics related to modeling the sensor measurements.

Citations

• An analysis of variance test for normality (complete samples)
• A Predictive Model using the Markov Property

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