Michael Paluszek - Practical MATLAB Deep Learning: A Project-Based Approach
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- Book:Practical MATLAB Deep Learning: A Project-Based Approach
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Along the way, youll learn to model complex systems, including the stock market, natural language, and angles-only orbit determination. Youll cover dynamics and control, and integrate deep-learning algorithms and approaches using MATLAB. Youll also apply deep learning to aircraft navigation using images.
Finally, youll carry out classification of ballet pirouettes using an inertial measurement unit to experiment with MATLABs 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.
Michael Paluszek: author's other books
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Any source code or other supplementary material referenced by the author in this book is available to readers on GitHub via the books product page, located at www.apress.com/9781484251232 . For more detailed information, please visit http://www.apress.com/source-code .
The authors would like to thank Eric Ham for suggesting LSTMs and also the idea for Chapteron Tokamak control. Thanks to Kestras Subacius of the MathWorks for tech support on the bluetooth device. We would also like to thank Matt Halpin for reading the book from front to end.
We would like to thank dancers Shaye Firer, Emily Parker, (Ryoko Tanaka) and Matanya Solomon for being our experimental subjects in this book. We would also like to thank the American Repertory Ballet and Executive Director Julie Hench for hosting our Chapterexperiment.
is President of Princeton Satellite Systems, Inc. (PSS) in Plainsboro, New Jersey. Mr. Michael founded PSS in 1992 to provide aerospace consulting services. He used MATLAB to develop the control system and simulations for the IndoStar-1 geosynchronous communications satellite. This led to the launch of Princeton Satellite Systems first commercial MATLAB toolbox, the Spacecraft Control Toolbox, in 1995. Since then he has developed toolboxes and software packages for aircraft, submarines, robotics, and nuclear fusion propulsion, resulting in Princeton Satellite Systems current extensive product line. He is working with the Princeton Plasma Physics Laboratory on a compact nuclear fusion reactor for energy generation and space propulsion.
Prior to founding PSS, Mr. Michael was an engineer at GE, Astro Space in East Windsor, NJ. At GE he designed the Global Geospace Science Polar despun platform control system and led the design of the GPS IIR attitude control system, the Inmarsat-3 attitude control systems, and the Mars Observer delta-V control system, leveraging MATLAB for control design. Mr. Michael also worked on the attitude determination system for the DMSP meteorological satellites. He flew communication satellites on over 12 satellite launches, including the GSTAR III recovery, the first transfer of a satellite to an operational orbit using electric thrusters. At Draper Laboratory, Mr. Michael worked on the Space Shuttle, Space Station, and submarine navigation. His Space Station work included designing of Control Moment Gyro-based control systems for attitude control.
Mr. Michael received his bachelors degree in Electrical Engineering and masters and engineers degrees in Aeronautics and Astronautics from the Massachusetts Institute of Technology. He is author of numerous papers and has over a dozen US patents. Mr. Michael is the author ofMATLAB Recipes,MATLAB Machine Learning,andMATLAB Machine Learning Recipes: A Problem-Solution Approach,all published by Apress.
is Vice President of Princeton Satellite Systems, Inc. in Plainsboro, New Jersey. She received her bachelors and masters degrees in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 1999 and 2001. Ms. Stephanie was introduced to the PSS Spacecraft Control Toolbox for MATLAB during a summer internship in 1996 and has been using MATLAB for aerospace analysis ever since. In her nearly 20 years of MATLAB experience, she has developed many software tools including the Solar Sail Module for the Spacecraft Control Toolbox, a proximity satellite operations toolbox for the Air Force, collision monitoring Simulink blocks for the Prisma satellite mission, and launch vehicle analysis tools in MATLAB and Java. She has developed novel methods for space situation assessment such as a numeric approach to assessing the general rendezvous problem between any two satellites implemented in both MATLAB and C++. Ms. Stephanie has contributed to PSSSpacecraft Attitude and Orbit Controltextbook, featuring examples using the Spacecraft Control Toolbox, and written many software user guides. She has conducted SCT training for engineers from diverse locales such as Australia, Canada, Brazil, and Thailand and has performed MATLAB consulting for NASA, the Air Force, and the European Space Agency. Ms. Stephanie is the author ofMATLAB Recipes,MATLAB Machine Learning,andMATLAB Machine Learning Recipes: A Problem-Solution Approach,published by Apress. In 2016, Ms. Stephanie was named a NASA NIAC Fellow for the project Fusion-Enabled Pluto Orbiter and Lander.
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