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Nonlinear System Identification

From Classical Approaches to Neural Networks, Fuzzy Models, and Gaussian Processes

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  • 1225pages
  • 43 heures de lecture

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Engineers and scientists will gain a comprehensive understanding of nonlinear system identification principles, enabling them to confidently apply the discussed models and methods to real-world problems. The book also highlights potential challenges that practitioners may encounter, ensuring a well-rounded grasp of the subject matter.

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Nonlinear System Identification, Oliver Nelles

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Année de publication
2023
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