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When building complex dynamic systems, certain lesser-known, poorly understood processes are typically ignored because of limitations in analytical skills and computational capacity. This ignorance always results in uncertainty in dynamic systems. This uncertainty or randomness may have an important influence on the global or local evolution of such systems. Therefore, it is critical to account for randomness in the mathematical modeling of complex dynamic systems. Stochastic dynamic systems are typically appropriate models for such randomly influenced systems and have come to play an important role in many branches of science and industry.

Special focus on modeling, analysis and control of stochastic systems