A new and fast nonlinear method for association analysis of biosignals

In this paper, we present some original theoretical aspects of a fast nonlinear association measure based on the work of Cramér. The features of this new measure--the V measure--when applied to biosignals are also shown using simulated time series. A comparative study with other well-known association measures available in the literature of biosignals is presented. V was found to be twice as fast and more robust to nonlinearities than the classical cross-correlation ratio (r2) and more than 100 times faster than the nonlinear regression coefficient (h2), presenting similar behavior in the presence of nonlinear simulated situations. This new measure is very fast and versatile. It is appropriate to deal with nonlinear relations presenting usually a sharp peak in the association function enabling a high degree of selectivity for maxima detection. It seems to constitute an improvement over linear methods of association which is faster and more robust to the existing nonlinearities. It can be used as an alternative to more complex nonlinear association measures when computational speed is an important feature.