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Matlab Machine Learning Recipes


Matlab Machine Learning Recipes
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Matlab Machine Learning Recipes


Matlab Machine Learning Recipes
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Author : Michael Paluszek
language : en
Publisher: Apress
Release Date : 2019-01-31

Matlab Machine Learning Recipes written by Michael Paluszek and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-31 with Computers categories.


Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem. All code in MATLAB Machine Learning Recipes: A Problem-Solution Approach is executable. The toolbox that the code uses provides a complete set of functions needed to implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow the reader to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. What you'll learn: How to write code for machine learning, adaptive control and estimation using MATLAB How these three areas complement each other How these three areas are needed for robust machine learning applications How to use MATLAB graphics and visualization tools for machine learning How to code real world examples in MATLAB for major applications of machine learning in big data Who is this book for: The primary audiences are engineers, data scientists and students wanting a comprehensive and code cookbook rich in examples on machine learning using MATLAB.



Matlab Machine Learning Recipes


Matlab Machine Learning Recipes
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Author : Michael Paluszek
language : en
Publisher: Springer Nature
Release Date : 2024-03-01

Matlab Machine Learning Recipes written by Michael Paluszek and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-01 with Computers categories.


Harness the power of MATLAB to resolve a wide range of machine learning challenges. This new and updated third edition provides examples of technologies critical to machine learning. Each example solves a real-world problem, and all code provided is executable. You can easily look up a particular problem and follow the steps in the solution. This book has something for everyone interested in machine learning. It also has material that will allow those with an interest in other technology areas to see how machine learning and MATLAB can help them solve problems in their areas of expertise. The chapter on data representation and MATLAB graphics includes new data types and additional graphics. Chapters on fuzzy logic, simple neural nets, and autonomous driving have new examples added. And there is a new chapter on spacecraft attitude determination using neural nets. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow you to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. What You Will Learn Write code for machine learning, adaptive control, and estimation using MATLAB Use MATLAB graphics and visualization tools for machine learning Become familiar with neural nets Build expert systems Understand adaptive control Gain knowledge of Kalman Filters Who This Book Is For Software engineers, control engineers, university faculty, undergraduate and graduate students, hobbyists.



Practical Matlab Deep Learning


Practical Matlab Deep Learning
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Author : Michael Paluszek
language : en
Publisher: Apress
Release Date : 2020-02-07

Practical Matlab Deep Learning written by Michael Paluszek and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-07 with Computers categories.


Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. You’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. Along the way, you'll learn to model complex systems, including the stock market, natural language, and angles-only orbit determination. You’ll cover dynamics and control, and integrate deep-learning algorithms and approaches using MATLAB. You'll also apply deep learning to aircraft navigation using images. Finally, you'll carry out classification of ballet pirouettes using an inertial measurement unit to experiment with MATLAB's hardware capabilities. What You Will Learn Explore deep learning using MATLAB and compare it to algorithms Write a deep learning function in MATLAB and train it with examples Use MATLAB toolboxes related to deep learning Implement tokamak disruption prediction Who This Book Is For Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.



Adcs Spacecraft Attitude Determination And Control


Adcs Spacecraft Attitude Determination And Control
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Author : Michael Paluszek
language : en
Publisher: Elsevier
Release Date : 2023-04-27

Adcs Spacecraft Attitude Determination And Control written by Michael Paluszek and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-27 with Technology & Engineering categories.


ADCS - Spacecraft Attitude Determination and Control provides a complete introduction to spacecraft control. The book covers all elements of attitude control system design, including kinematics, dynamics, orbits, disturbances, actuators, sensors, and mission operations. Essential hardware details are provided for star cameras, reaction wheels, sun sensors, and other key components. The book explores how to design a control system for a spacecraft, control theory, and actuator and sensor details. Examples are drawn from the author's 40 years of industrial experience with spacecraft such as GGS, GPS IIR, Mars Observer, and commercial communications satellites, and includes historical background and real-life examples. - Features critical details on hardware and the space environment - Combines theory and ready-to-implement practical algorithms - Includes MATLAB code for all examples - Provides plots and figures generated with the included code



Matlab Machine Learning


Matlab Machine Learning
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Author : Michael Paluszek
language : en
Publisher: Apress
Release Date : 2016-12-28

Matlab Machine Learning written by Michael Paluszek and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-28 with Computers categories.


This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It provides descriptions of all major areas in machine learning. The book reviews commercially available packages for machine learning and shows how they fit into the field. The book then shows how MATLAB can be used to solve machine learning problems and how MATLAB graphics can enhance the programmer’s understanding of the results and help users of their software grasp the results. Machine Learning can be very mathematical. The mathematics for each area is introduced in a clear and concise form so that even casual readers can understand the math. Readers from all areas of engineering will see connections to what they know and will learn new technology. The book then providescomplete solutions in MATLAB for several important problems in machine learning including face identification, autonomous driving, and data classification. Full source code is provided for all of the examples and applications in the book. What you'll learn: An overview of the field of machine learning Commercial and open source packages in MATLAB How to use MATLAB for programming and building machine learning applications MATLAB graphics for machine learning Practical real world examples in MATLAB for major applications of machine learning in big data Who is this book for: The primary audiences are engineers and engineering students wanting a comprehensive and practical introduction to machine learning.



Network Modeling Simulation And Analysis In Matlab


Network Modeling Simulation And Analysis In Matlab
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Author : Dac-Nhuong Le
language : en
Publisher: John Wiley & Sons
Release Date : 2019-08-13

Network Modeling Simulation And Analysis In Matlab written by Dac-Nhuong Le and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-13 with Computers categories.


The purpose of this book is first to study MATLAB programming concepts, then the basic concepts of modeling and simulation analysis, particularly focus on digital communication simulation. The book will cover the topics practically to describe network routing simulation using MATLAB tool. It will cover the dimensions' like Wireless network and WSN simulation using MATLAB, then depict the modeling and simulation of vehicles power network in detail along with considering different case studies. Key features of the book include: Discusses different basics and advanced methodology with their fundamental concepts of exploration and exploitation in NETWORK SIMULATION. Elaborates practice questions and simulations in MATLAB Student-friendly and Concise Useful for UG and PG level research scholar Aimed at Practical approach for network simulation with more programs with step by step comments. Based on the Latest technologies, coverage of wireless simulation and WSN concepts and implementations



Image Processing Recipes In Matlab


Image Processing Recipes In Matlab
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Author : Oge Marques
language : en
Publisher: CRC Press
Release Date : 2024-05-16

Image Processing Recipes In Matlab written by Oge Marques and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-16 with Computers categories.


Leveraging the latest developments in MATLAB and its image processing toolbox, this 'cookbook' is a collection of 30 practical recipes for image processing, ranging from foundational techniques to recently published algorithms. Presented in a clear and meaningful sequence, these recipes are prepared with the reader in mind, allowing one to focus on particular topics or read as a whole from cover to cover. Key Features: A practical, user-friendly guide that equips researchers and practitioners with the tools to implement efficient image processing workflows in MATLAB. Each recipe is presented through clear, step-by-step instructions and rich visual examples. Each recipe contains its own source code, explanations, and figures, making the book an excellent standalone resource for quick reference. Strategically structured to aid sequential learning, yet with self-contained chapters for those seeking solutions to specific image processing challenges. The book serves as a concise and readable practical reference to deploy image processing pipelines in MATLAB quickly and efficiently. With its accessible and practical approach, the book is a valuable guide for those who navigate this evolving area, including researchers, students, developers, and practitioners in the fields of image processing, computer vision, and image analysis.



Intelligent Learning Approaches For Renewable And Sustainable Energy


Intelligent Learning Approaches For Renewable And Sustainable Energy
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Author : Josep M. Guerrero
language : en
Publisher: Elsevier
Release Date : 2024-02-21

Intelligent Learning Approaches For Renewable And Sustainable Energy written by Josep M. Guerrero and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-21 with Computers categories.


Intelligent Learning Approaches for Renewable and Sustainable Energy provides a practical, systematic overview of the application of advanced intelligent control techniques, adaptive techniques, machine learning algorithms, and predictive control in renewable and sustainable energy.The book begins by introducing the intelligent learning approaches, and the roles of artificial intelligence and machine learning in terms of energy and sustainability, grid transformation, large-scale integration of renewable energy, and variability and flexibility of renewable sources. The second section of the book provides detailed coverage of intelligent learning techniques as applied to key areas of renewable and sustainable energy, including forecasting, supply and demand, integration, energy management, and optimization, supported by case studies, figures, schematics, and references.This is a useful resource for researchers, scientists, advanced students, energy engineers, R&D professionals, and other industrial personnel with an interest in sustainable energy and integration of renewable energy sources, energy systems, energy engineering, machine learning, and artificial intelligence. - Explores cutting-edge intelligent techniques and their implications for future energy systems development - Opens the door to a range of applications across forecasting, supply and demand, energy management, optimization, and more - Includes a range of case studies that provide insights into the challenges and solutions in real-world applications



Aeronautics And Astronautics


Aeronautics And Astronautics
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Author : Sergio De Rosa
language : en
Publisher: Materials Research Forum LLC
Release Date : 2023-12-15

Aeronautics And Astronautics written by Sergio De Rosa and has been published by Materials Research Forum LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-15 with Technology & Engineering categories.


These conference proceedings present 165 papers in all scientific and aerospace engineering fields, including materials and structures, aerodynamics and fluid dynamics, propulsion, aerospace systems, flight mechanics and control, space systems, and missions. Keywords: Aerospace Shell Structures, MCAST's Aerospace Program, Sandwich Structures, Thermal Buckling, Simulation of Elastodynamic Problems. Statically Deflected Beam, Meshes with Arbitrary Polygons, Variable Stiffness Composite Panels, Mechanical Response of Composites, 3D Printing Technique, Hygrothermal Effects in Composite Materials, Freeze-Thaw Cycling, Polymer Matrices, Morphing Aileron, Thermo-Elastic Homogenization of Polycrystals, Flutter Instability in Elastic Structures, Adaptive Composite Wings, Cylindrical IGA Patches, TRAC Longerons, Structural Damage Detection, Fatigue Behavior of Stiffened Composite Components, Redesign of Composite Fuselage Barrel Components, Damage Modelling of Metallic Lattice Materials, Ceramic Matrix Composites, Peridynamics Elastoplastic Model, Structural Batteries Challenges. Dynamic Buckling Structural Test, Delamination Identification on Composites Panels. CubeSat Radiative Surface, Wind Tunnel Testing.



Deep Learning For Medical Decision Support Systems


Deep Learning For Medical Decision Support Systems
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Author : Utku Kose
language : en
Publisher: Springer Nature
Release Date : 2020-06-17

Deep Learning For Medical Decision Support Systems written by Utku Kose and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-17 with Technology & Engineering categories.


This book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today’s problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation.