MODEL IMPERFECTION AND PREDICTING PREDICTABILITY.

It has been argued that Lyapunov exponents as a measure of predictability are of limited value because they only provide a global average. Characterizing an attractor by a distribution of times for initial uncertainties to increase by a factor of q has been suggested as a more useful alternative. These have found favor in some applications, despite assumptions of the fictitious perfect model scenario. Here, an electronic circuit, which offers a good test-bed for addressing predictability in the imperfect model scenario, is presented. A novel measure of predictability is presented and implications of model imperfection on characterizing the dynamics of chaotic systems are discussed. It is a case for a multiple model approach. [ABSTRACT FROM AUTHOR]