An Analysis of Information Dynamic Behavior Using Autoregressive Models

An Analysis of Information Dynamic Behavior Using Autoregressive Models

Blog Article

Information Theory is a branch of mathematics, more specifically probability theory, that p32 can opener studies information quantification.Recently, several researches have been successful with the use of Information Theoretic Learning (ITL) as a new technique of unsupervised learning.In these works, information measures are used as criterion of optimality in learning.In this article, we will analyze a still unexplored aspect of these information measures, their dynamic behavior.Autoregressive models (linear and non-linear) will be used opi mauvnetic poles to represent the dynamics in information measures.

As a source of dynamic information, videos with different characteristics like fading, monotonous sequences, etc., will be used.