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Michael Paluszek is President of Princeton Satellite Systems, Inc. (PSS) in Plainsboro, New Jersey. Mr. Paluszek 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. Mr. Paluszek is a lecturer at the Massachusetts Institute of Technology.
At Draper Laboratory Mr. Paluszek worked on the Space Shuttle, Space Station, and submarine naviga- tion. His Space Station work included designing Control Moment Gyro-based control systems for attitude control.
Mr. Paluszek received his bachelor's degree in Electrical Engineering, and master's and engineer's degrees in Aeronautics and Astronautics from the Massachusetts Institute of Technology. He is the author of numerous papers and has over a dozen U.S. Patents. Mr. Paluszek is the author of "MATLAB Recipes", "MATLAB Machine Learning," "Practical MATLAB Deep Learning, A Projects-Based Approach, Second Edition," all published by Apress, and "ADCS: Spacecraft Attitude Determination and Control Systems by Elsevier."
Stephanie Thomas is Vice President of Princeton Satellite Systems, Inc. in Plainsboro, New Jersey. She received her bachelor's and master's degrees in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 1999 and 2001. Ms. Thomas 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
Chapter 1. An Overview of Machine Learning.- Chapter 2. Data Representation.- Chapter 3. MATLAB Graphics.- Chapter 4. Kalman Filters.- Chapter 5. Adaptive Control.- Chapter 6. Neural Aircraft Control.- Chapter 7. Fuzzy Logic.- Chapter 8. Classification with Neural Nets.- Chapter 9. Simple Neural Nets.- Chapter 10. Data Classification. - Chapter 11. Neural Nets with Deep Learning.- Chapter 12. Multiple Hypothesis Testing.- Chapter 13. Autonomous Driving with MHT.- Chapter 14. Case-Based Expert Systems.- Chapter 15. Spacecraft Attitude Determination Using Neural Nets. -Appendix A Brief History of Autonomous Learning.- Appendix B. Software for Autonomous Learning.
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