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Nonlinear System Identification

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

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  • 1225 pages
  • 43 hours of reading

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Engineers and scientists will gain a comprehensive understanding of nonlinear system identification principles, enabling them to confidently apply various models and methods to real-world challenges. The book emphasizes practical application while addressing potential difficulties that practitioners may encounter, making it a valuable resource for both academia and industry.

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Nonlinear System Identification, Oliver Nelles

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Released
2022
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(Hardcover)
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