Data-Driven Science and Engineering

Data-Driven Science and Engineering
Author: Steven L. Brunton
Publisher: Cambridge University Press
Total Pages: 615
Release: 2022-05-05
Genre: Computers
ISBN: 1009098489

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A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLABĀ®.


Data-based Modelling of Nonlinear Systems for Control
Language: en
Pages: 226
Authors: Gregor Gregorcic
Categories: Nonlinear systems
Type: BOOK - Published: 2004 - Publisher:

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This work presented here, investigates in depth the techniques for modelling of unknown nonlinear dynamic systems from their observed input-output behaviour. Th
Artificial Neural Networks for Modelling and Control of Non-Linear Systems
Language: en
Pages: 242
Authors: Johan A.K. Suykens
Categories: Technology & Engineering
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

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Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear sys
Sampled-Data Models for Linear and Nonlinear Systems
Language: en
Pages: 288
Authors: Juan I. Yuz
Categories: Technology & Engineering
Type: BOOK - Published: 2013-10-17 - Publisher: Springer Science & Business Media

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Sampled-data Models for Linear and Nonlinear Systems provides a fresh new look at a subject with which many researchers may think themselves familiar. Rather th
Adaptive Learning Methods for Nonlinear System Modeling
Language: en
Pages: 390
Authors: Danilo Comminiello
Categories: Technology & Engineering
Type: BOOK - Published: 2018-06-11 - Publisher: Butterworth-Heinemann

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Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for no
Data-Driven Science and Engineering
Language: en
Pages: 615
Authors: Steven L. Brunton
Categories: Computers
Type: BOOK - Published: 2022-05-05 - Publisher: Cambridge University Press

GET EBOOK

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLABĀ®.