Stochastic processes are those probabilistic tools used to approximate uncertainty. With the advent of the computer, uncertainty which is inherent in large complex systems can be approximated. Advances in space science, communications systems and many of the defence initiatives, not to mention robotics and artificial intelligence, have come about because of the ability of the computer to solve massive probabilistic calculations to account for uncertainty in the system being adjusted. This text applies the most recent advances in stochastic and probabilistic processes to areas such as communications and robotic technology. The author also uses the thermodynamic principle of entropy to measure and analyze uncertainty in various systems.
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GEORGE N. SARIDIS is Professor of Electrical Engineering and Director of the Robotics and Automation Laboratories at Rensselaer Polytechnic Institute. Recognized throughout the world as one of the foremost theoreticians in robotics, automation, and systems engineering, Professor Saridis has received numerous honors, including the Founding President Award of the IEEE and the IEEE Centennial Medal. He has served as Program Director of the Systems Theory and Applications Program in the Engineering Division of the National Science Foundation. Among his publications are Intelligent Robotic Systems: Theory, Design, and Applications (with K. P. Valavanis) and Self-Organizing Control of Stochastic Systems. Dr. Saridis is a member of the editorial board of Journal of Robotic Systems, published by Wiley.
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