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Can I read Reconciling Deep Learning and Control Theory: Recurrent Neural Networks for Indirect Data-Driven Control on EtoBox?
Reconciling Deep Learning and Control Theory: Recurrent Neural Networks for Indirect Data-Driven Control by Fabio Bonassi is a engineering available to read on EtoBox.
What is Reconciling Deep Learning and Control Theory: Recurrent Neural Networks for Indirect Data-Driven Control about?
<p>This open access book presents outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collabor
Who reads Reconciling Deep Learning and Control Theory: Recurrent Neural Networks for Indirect Data-Driven Control?
It is typically read by working professionals who need an authoritative practice reference.
Common subject areas: medicine, law, business, engineering.
- Author
- Fabio Bonassi
- Publisher
- Springer Nature Switzerland AG
- Published
- 2024
- Language
- EN
- ISBN
- 9783031514999
- Category
- engineering
- Subjects
- Engineering, Computer Science, Medical
- Updated
- 2026-03-25
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