Written in two parts, the first revises the ideas and theoretical bases necessary for a good understanding of the techniques used in the second, which deals with applications of MATLAB(R) and SIMULINK(R) in process control and digital signal processing. Each application is treated through various techniques including the classical methods of automation and of deterministic and random digital processing using fuzzy logic and neural networks. The preceding mathematical study of the physical processes goes from finding the equations to editing the analogical model. The following SIMULINK(R) toolbox functions and blocks have been used: Control System, Signal Processing, Neural Network and Fuzzy Logic.
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Written in two parts, the first revises the ideas and theoretical bases necessary for a good understanding of the techniques used in the second, which deals with applications of MATLAB(R) and SIMULINK(R) in process control and digital signal processing. Each application is treated through various techniques including the classical methods of automation and of deterministic and random digital processing using fuzzy logic and neural networks. The preceding mathematical study of the physical processes goes from finding the equations to editing the analogical model. The following SIMULINK(R) toolbox functions and blocks have been used: Control System, Signal Processing, Neural Network and Fuzzy Logic.
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