Authors

Title

Risk Overbounding for a Linear Model

In

Proceedings of the 21th conference DCCN 2018, Distributed Computer and Communication Networks. DCCN 2018. Communications in Computer and Information Science

Volume

919

Pages

157–169

Publisher

Springer, Cham

Year

2018

Indexed by

Abstract

For some safety-critical applications, the risk indicator is rep-
resented as a time series of estimation errors in the case of a linear model.
The safety of the system is compromised if the probability that this risk
indicator leaves a given confidence zone at least once during a certain
period becomes too important. Sometimes, we are also interested in the
calculation of the instantaneous risk probability. The main difficulty is
that the Cumulative Distribution Functions (CDFs) (with infinite sup-
port) of measurement noise in the above-mentioned linear model are un-
known and only their upper and lower bounds are available. The present
paper continues the study of previously developed conservative bounds
for the above-mentioned risk probabilities as functions of the bounds for
the measurement noise CDFs. The original contribution of the present
paper consists in the generalization of the previously obtained results to
the case of a linear model.

Affiliations

Offprint