Nadipuram R. Prasad1, Salvador Almanza-Garcia1, Thomas T. Lu2
CMC-Computers, Materials & Continua, Vol.14, No.1, pp. 1-22, 2009, DOI:10.3970/cmc.2009.014.001
Abstract The paper presents a revolutionary framework for the modeling, detection, characterization, identification, and machine-learning of anomalous behavior in observed phenomena arising from a large class of unknown and uncertain dynamical systems. An evolved behavior would in general be very difficult to correct unless the specific anomalous event that caused such behavior can be detected early, and any consequence attributed to the specific anomaly following its detection. Substantial investigative time and effort is required to back-track the cause for abnormal behavior and to recreate the event sequence leading to such abnormal behavior. The need to automatically detect anomalous behavior is therefore… More >
Login
Register
