Abstract: An exemplary method for analyzing behavior of a system includes receiving dynamical measurement data regarding the system, applying a quadratically constrained quadratic 0-1 problem to identify data among the received data, and storing the identified data. An exemplary seizure warning method includes continuously calculating STLmax values, identifying critical sites by applying a quadratically constrained quadratic 0-1 solution to data (e.g. STLmax profiles) derived from pre-seizure onset and post-seizure onset EEG signals, monitoring a T-index curve of the identified critical sites, warning of an impending seizure, observing a seizure and then repeating the cycle by identifying critical sites using the new data, and then monitoring them.

Abstract: Characterizing the behavior of a chaotic, multi-dimensional system is achieved by measuring each of a number of signals associated with the system, and generating therefrom, a spatio-temporal response based on each signal. Multiple dynamical profiles are then generated for each spatio-temporal response, where each of the multiple dynamical profiles correspond to a different one of multiple dynamical parameters. Over a period of time, a determination is made as to whether a certain level of dynamic entrainment and/or disentrainment exists between the dynamical profiles associated with a selected one or a selected combination of dynamical parameters. Seizure warnings and/or predictions are provided based on this determination.

Abstract: Techniques for investigating dynamical behavior of complex systems for monitoring, diagnosing, and predicting future behavior and trends are presented. A method includes generating a multi-dimensional representation for each signal acquired from corresponding channels of a multi-dimensional system, and generating dynamical profiles for each channel in accordance with one of multiple dynamical metrics. The method includes calculating multiple first statistical measures for a group of the channels that reflect a level of interaction among the channel group associated with at least one of the metrics. The method includes calculating in an initialization period a second statistical measure for each of the first statistical measures that reflect the association of the first statistical measures with related occurrences under investigation.