Modeling and processing daily thermometry data

The article considers the class of mathematical models of daily thermometry of thermal homeostasis of a healthy person, defined in the state space by discrete linear stochastic systems. For third-order models the daily average temperature (mesor) is modeled as an unknown input effect. The state vector of the model includes the value of body temperature at discrete time instants. In case when the average temperature is unknown when modeling the process of discrete filtering of thermometry data for third- order models, it is proposed to use the Gillijns-Moor algorithm (S. Gillijns, B. De Moor) instead of a discrete Kalman filter.