MATLAB Machine Learning Recipes: A Problem-Solution Approach 3rd

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.

利用MATLAB的強大功能來解決各種機器學習挑戰。這本新的第三版已經更新，提供了解決機器學習所需的關鍵技術的示例。每個示例都解決了一個現實世界的問題，並且提供的所有代碼都可以執行。您可以輕鬆查找特定問題並按照解決方案的步驟進行操作。

這本書對於所有對機器學習感興趣的人都有所收穫。它還提供了其他技術領域感興趣的人了解機器學習和MATLAB如何幫助他們解決專業領域問題的材料。關於數據表示和MATLAB圖形的章節包括了新的數據類型和額外的圖形。模糊邏輯、簡單神經網絡和自動駕駛的章節增加了新的示例。還新增了一章關於使用神經網絡進行航天器姿態確定的內容。作者Michael Paluszek和Stephanie Thomas展示了所有這些技術如何讓您構建複雜的應用程序，以解決模式識別、自動駕駛、專家系統等問題。

您將學到什麼：
- 使用MATLAB編寫機器學習、自適應控制和估計的代碼
- 使用MATLAB圖形和可視化工具進行機器學習
- 熟悉神經網絡
- 構建專家系統
- 理解自適應控制
- 獲得卡爾曼濾波器的知識

適合閱讀對象：
軟體工程師、控制工程師、大學教師、本科和研究生學生、愛好者。

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.

propulsion. He is also leading the development of new power electronics for fusion power systems and working on heat-engine-based auxiliary power systems for spacecraft.

Prior to founding PSS, Mr. Paluszek 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. Paluszek also worked on the attitude determination system for the DMSP meteorological satellites. Mr. Paluszek flew communication satellites on over twelve satellite launches, including the GSTAR III recovery, the first transfer of a satellite to an operational orbit using electric thrusters.

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

a numeric approach to assessing the general rendezvous problem between any two satellites implemented in both MATLAB and C++. Ms. Thomas has contributed to PSS' Attitude and Orbit Control textbook, featuring examples using the Spacecraft Control Toolbox, and written many software User's 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. Thomas is the author of "MATLAB Recipes" and "MATLAB Machine Learning" and "Practical MATLAB Deep Learning Projects" and 'Practical MATLAB Deep Learning Projects Version 2" published by Apress. In 2016, Ms. Thomas was named a NASA NIAC Fellow for the project "Fusion-Enabled Pluto Orbiter and Lander". Stephanie is an Associate Fellow of the AIAA and a member of the AIAA Propulsion and Energy Group.

Michael Paluszek是新澤西州普萊恩斯博羅的Princeton Satellite Systems, Inc. (PSS)的總裁。Paluszek先生於1992年創立了PSS，提供航天諮詢服務。他使用MATLAB開發了Indostar-1地球同步通信衛星的控制系統和模擬器。這導致了Princeton Satellite Systems於1995年推出了第一個商業MATLAB工具箱，即Spacecraft Control Toolbox。自那時以來，他開發了用於飛機、潛艇、機器人和核融合推進的工具箱和軟件包，從而形成了Princeton Satellite Systems目前廣泛的產品線。他正在與普林斯頓等離子物理實驗室合作開發一種用於能源生成和太空的小型核融合反應堆。Paluszek先生還是麻省理工學院的講師。

在創立PSS之前，Paluszek先生曾在新澤西州伊斯特溫莎的GE Astro Space擔任工程師。在GE，他設計了全球地球空間科學極地去旋平台控制系統，並領導了GPS IIR姿態控制系統、Inmarsat-3姿態控制系統和火星觀測者增量速度控制系統的設計，利用MATLAB進行控制設計。Paluszek先生還參與了DMSP氣象衛星的姿態確定系統。Paluszek先生參與了超過12次衛星發射的通信衛星飛行任務，包括GSTAR III的回收，這是首次使用電推進器將衛星轉移到運行軌道上。

在Draper實驗室，Paluszek先生從事太空梭、太空站和潛艇導航的工作。他的太空站工作包括設計基於控制力矩陀螺的姿態控制系統。

Paluszek先生在麻省理工學院獲得了電機工程學士學位，以及航空航天學碩士和工程師學位。他是許多論文的作者，擁有十多項美國專利。Paluszek先生是Apress出版的《MATLAB Recipes》、《MATLAB Machine Learning》、《Practical MATLAB Deep Learning, A Projects-Based Approach, Second Edition》和《ADCS: Spacecraft Attitude Determination and Control Systems by Elsevier》的作者。

Stephanie Thomas是新澤西州普萊恩斯博羅的Princeton Satellite Systems, Inc.的副總裁。她於1999年和2001年在麻省理工學院獲得航空航天學士和碩士學位。Thomas女士在1996年的暑期實習期間首次接觸到PSS的MATLAB太空船控制工具箱，並從那時起一直在使用MATLAB進行航空航天分析。在近20年的MATLAB經驗中，她開發了許多軟件工具，包括Spacecraft Control Toolbox的Solar Sail模塊；為空軍開發的近距離衛星操作工具箱；Prisma衛星任務的碰撞監測Simulink模塊；以及MATLAB和Java中的發射載具分析工具。她還開發了用於太空情況評估的新方法，例如在MATLAB和C++中實現的任意兩個衛星之間的一般會合問題的數值方法。Thomas女士為PSS的姿態和軌道控制教材做出了貢獻，其中包括使用Spacecraft Control Toolbox的示例，並撰寫了許多軟件使用者指南。她曾為來自澳大利亞、加拿大、巴西和泰國等不同地方的工程師進行SCT培訓，並為NASA、空軍和歐洲太空總署提供MATLAB諮詢服務。Thomas女士是Apress出版的《MATLAB Recipes》、《MATLAB Machine Learning》、《Practical MATLAB Deep Learning Projects》和《Practical MATLAB Deep Learning Projects Version 2》的作者。2016年，Thomas女士被NASA任命為