Michael Paluszek – författare
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14 produkter
14 produkter
E-bok
Engelska, 20232 332 kr
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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
Häftad, Engelska, 2023
1 639 kr
Skickas inom 10-15 vardagar
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
Häftad, Engelska, 2026
2 947 kr
Kommande
Advanced Space Propulsion: Technologies, Missions, and Computer Modeling includes coverage of all these topics in an integrated manner. The volume, written by a team of sector-specific R&D experts, touches upon fundamentals cardinal to the understanding of [i] Orbit theory and its implications for control, estimation, and optimization of trajectory and attitude, and [ii] How each mission is designed (depending primarily on the mass of the payload, but also on how far from Earth the launch vehicle needs to go), and then succeeds in consolidating them with software and computer applications for simulations and modeling. The book continues with a discussion on the complete gamut of in-space propulsion power sources and concludes with both human and robotic mission-related case studies and future implementation examples. The outcome is a carefully calibrated and self-contained resource that will prove to be invaluable for graduate and senior undergraduate students, researchers, scientists, and engineering professionals alike.Covers all advanced propulsion technologies, both existing and futureTakes advantage of a structured and comprehensive approach to seamlessly combine theory, technological outcomes, and their practical applicationsFeatures case studies and worked-out examples with MATLAB code
E-bok
PDF, Engelska, 2015896 kr
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Learn fromstate-of-the-art examples in robotics, motors, detection filters, chemicalprocesses, aircraft, and spacecraft. This is a practical reference for industryengineers using MATLAB to solve everyday problems. With MATLAB Recipes: AProblem-Solution Approach you will review contemporary MATLAB codingincluding the latest language features and use MATLAB as a software developmentenvironment including code organization, GUI development, and algorithm designand testing.
This book providespractical guidance for using MATLAB to build a body of code you can turn totime and again for solving technical problems in your line of work. Developalgorithms, test them, visualize the results, and pass the code along to othersto create a functional code base for your firm.
E-bok
Engelska, 2016652 kr
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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 learningCommercial and open source packages in MATLABHow to use MATLAB for programming and building machine learning applicationsMATLAB graphics for machine learningPractical real world examples in MATLAB for major applications of machine learning in big dataWho is this book for:The primary audiences are engineers and engineering students wanting a comprehensive and practical introduction to machine learning.
E-bok
Engelska, 2019652 kr
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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 MATLABHow these three areas complement each otherHow these three areas are needed for robust machine learning applicationsHow to use MATLAB graphics and visualization tools for machine learningHow 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.
E-bok
Engelska, 2020489 kr
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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 LearnExplore deep learning using MATLAB and compare it to algorithmsWrite a deep learning function in MATLAB and train it with examplesUse MATLAB toolboxes related to deep learningImplement tokamak disruption predictionWho This Book Is For Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.
Häftad, Engelska, 2021
616 kr
Skickas inom 10-15 vardagar
Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. With this book you will review contemporary MATLAB coding including the latest MATLAB language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. Features now covered include the new graph and digraph classes for charts and networks; interactive documents that combine text, code, and output; a new development environment for building apps; locally defined functions in scripts; automatic expansion of dimensions; tall arrays for big data; the new string type; new functions to encode/decode JSON; handling non-English languages; the new class architecture; the Mocking framework; an engine API for Java; the cloud-based MATLAB desktop; the memoize function; and heatmap charts. MATLAB Recipes: A Problem-Solution Approach, Second Edition provides practical, hands-on code snippets and guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm. What You Will LearnGet up to date with the latest MATLAB up to and including MATLAB 2020bCode in MATLABWrite applications in MATLABBuild your own toolbox of MATLAB code to increase your efficiency and effectivenessWho This Book Is For Engineers, data scientists, and students wanting a book rich in examples using MATLAB.
E-bok
Engelska, 2021870 kr
Läs direkt efter köp
Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. With this book you will review contemporary MATLAB coding including the latest MATLAB language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing.
Features now covered include the new graph and digraph classes for charts and networks; interactive documents that combine text, code, and output; a new development environment for building apps; locally defined functions in scripts; automatic expansion of dimensions; tall arrays for big data; the new string type; new functions to encode/decode JSON; handling non-English languages; the new class architecture; the Mocking framework; an engine API for Java; the cloud-based MATLAB desktop; the memoize function; and heatmap charts.
MATLAB Recipes: A Problem-Solution Approach, Second Edition provides practical, hands-on code snippets and guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm.
What You Will Learn
Get up to date with the latest MATLAB up to and including MATLAB 2020bCode in MATLAB Write applications in MATLAB Build your own toolbox of MATLAB code to increase your efficiency and effectivenessWho This Book Is For
Engineers, data scientists, and students wanting a book rich in examples using MATLAB.
Häftad, Engelska, 2022
616 kr
Skickas inom 10-15 vardagar
Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. In this book, you’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. This edition includes new and expanded projects, and covers generative deep learning and reinforcement learning.Over the course of the book, you'll learn to model complex systems and apply deep learning to problems in those areas. Applications include:Aircraft navigationAn aircraft that lands on Titan, the moon of Saturn, using reinforcement learningStock market predictionNatural language processingMusic creation usng generative deep learningPlasma controlEarth sensor processing for spacecraftMATLAB Bluetooth data acquisition applied to dance physics What You Will LearnExplore deep learning using MATLAB and compare it to algorithmsWrite a deep learning function in MATLAB and train it with examplesUse MATLAB toolboxes related to deep learningImplement tokamak disruption predictionNow includes reinforcement learningWho This Book Is For Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.
E-bok
Engelska, 2022896 kr
Läs direkt efter köp
Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MATLAB''s deep-learning toolboxes. In this book, you’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. This edition includes new and expanded projects, and covers generative deep learning and reinforcement learning.
Over the course of the book, you''ll learn to model complex systems and apply deep learning to problems in those areas. Applications include:
Aircraft navigationAn aircraft that lands on Titan, the moon of Saturn, using reinforcement learningStock market predictionNatural language processingMusic creation usng generative deep learningPlasma controlEarth sensor processing for spacecraftMATLAB Bluetooth data acquisition applied to dance physics What You Will LearnExplore deep learning using MATLAB and compare it to algorithmsWrite a deep learning function in MATLAB and train it with examplesUse MATLAB toolboxes related to deep learningImplement tokamak disruption predictionNow includes reinforcement learningWho This Book Is For Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.
Häftad, Engelska, 2024
565 kr
Skickas inom 5-8 vardagar
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 LearnWrite code for machine learning, adaptive control, and estimation using MATLABUse MATLAB graphics and visualization tools for machine learningBecome familiar with neural netsBuild expert systemsUnderstand adaptive controlGain knowledge of Kalman FiltersWho This Book Is ForSoftware engineers, control engineers, university faculty, undergraduate and graduate students, hobbyists.
E-bok
Engelska, 2024815 kr
Läs direkt efter köp
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 LearnWrite code for machine learning, adaptive control, and estimation using MATLABUse MATLAB graphics and visualization tools for machine learningBecome familiar with neural netsBuild expert systemsUnderstand adaptive controlGain knowledge of Kalman FiltersWho This Book Is ForSoftware engineers, control engineers, university faculty, undergraduate and graduate students, hobbyists.
Häftad, Engelska, 2026
664 kr
Kommande
Harness the power of MATLAB to resolve a wide range of the latest machine learning challenges. The enhanced Fourth Edition is updated with new chapters on advanced machine learning techniques and real-world engineering applications.This book offers broad appeal for anyone interested in machine learning, with a new introductory chapter on MATLAB for greater accessibility and a dedicated toolbox chapter to streamline modern workflows. It also demonstrates how MATLAB and machine learning can address challenges across various technical fields. New chapters cover key machine learning areas like pattern recognition, system identification, and computer vision, along with application-focused content on advanced engineering topics such as FPGA deployment, space missions, power electronics, and dynamic modeling. Each example in the book addresses a real-world problem, with fully executable code provided for every solution. You can quickly find and follow step-by-step guidance for specific challenges, enabling you to leverage these technologies to build sophisticated applications in areas such as pattern recognition, autonomous driving, expert systems, and more.What You Will LearnWrite code for machine learning, adaptive control, and estimation using MATLABUse MATLAB graphics and visualization tools for machine learningGain knowledge of Kalman FiltersBuild neural networks, including physics-informed modelsPerform system identification and build expert systemsWork with computer vision and autonomous systemsIntegrate neural networks to FPGA hardwareApply machine learning to remaining useful life predictionWho This Book Is ForSoftware engineers, control engineers, university faculty, undergraduate and graduate students, hobbyists.