Stochastic discretized learning-based weak estimation: a novel estimation method for non-stationary environments

作者：

Highlights：

• We present finite-memory estimation techniques for non-stationary environments.

• These new techniques use the principles of discretized Learning Automata.

• The results have been tested for many time-varying problems and applications.

摘要

Highlights•We present finite-memory estimation techniques for non-stationary environments.•These new techniques use the principles of discretized Learning Automata.•The results have been tested for many time-varying problems and applications.

论文关键词：Weak estimators,Learning automata,Non-stationary environments

论文评审过程：Received 23 April 2014, Revised 22 April 2016, Accepted 14 May 2016, Available online 21 May 2016, Version of Record 20 June 2016.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.05.001