MATRIX MINI AI工業機器人：使用MATRIXblock圖控軟體，含WRO國際奧林匹亞機器人暨MARC賽事- 附贈MOSME行動 (1版)
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【簡介】
本書是針對 MATRIX機器人學習套件與Arduino程式設計的綜合學習指南，專門為初學者及進階學習者設計。結合了機器人的硬體組裝與軟體設計，透過任務執行的教學方式，幫助學習者從基礎知識入門，進行機器人的自主設計與操作。書中不僅包括了機器人的基礎概念、技術知識，並涵蓋了國際機器人競賽的規則與準備技巧，幫助學習者輕鬆參加競賽。
【目錄】
第一篇 MATRIX MR3000 基礎入門
Chapter 1 機器人與 MATRIX
1-1 什麼是機器人
1-2 MATRIX MINI 套件與Arduino 介紹
1-3 MATRIX Parts
1-4 MATRIX 組裝方式
課後習題
Chapter 2 RGB LED 控制
2-1 控制RGB LED
2-2 程式設計：模擬警車車燈、彩虹閃爍燈
課後習題
Chapter 3 閃爍的呼吸燈：RGB 控制（變數）
3-1 變數方塊使用
3-2 程式設計：閃爍的呼吸燈
課後習題
第二篇 MATRIX機器人應用
Chapter 4 MATRIX機器人的九種應用
4-1 MATRIX 手推車
4-2 MATRIX 翹翹板
4-3 MATRIX 雨刷
4-4 MATRIX 按摩槍
4-5 MATRIX 摩天輪
4-6 MATRIX 投石機
4-7 MATRIX 自動門
4-8 MATRIX 電動柵欄門
4-9 MATRIX 仿生獸
課後習題
Chapter 5 MATRIX小車機器人組裝
5-1 小車機器人介紹
5-2 組裝基本車
5-3 前進，後退，轉彎
5-4 程式設計：三種轉彎方式
5-5 挑戰題目：車輛操縱S 形、車輛操縱正方形、車輛操縱折返跑
課後習題
Chapter 6 MATRIX小車機器人互動與程式控制
6-1 跟著黑線走
6-2 避開障礙物
6-3 加速、換檔、推進器
6-4 打開開關：按鈕控制（條件）
6-5 小幫手：自訂指令方塊（函式）
課後習題
第三篇 MATRIX機器人進階應用（需選購充包）
Chapter 7 避開障礙物：微動開關
7-1 微動開關
7-2 避障車組裝設計
課後習題
Chapter 8 伺服馬達
8-1 認識伺服馬達
8-2 清除障礙：伺服馬達清障車組裝
課後習題
Chapter 9 卡車
9-1 連桿機構
9-2 連桿機構設計及應用任務
課後習題
第四篇 機器人挑戰賽與創新競賽
Chapter 10 START! AI 智慧小車競賽
10-1 START ！ AI 智慧小車競賽規則
10-2 比賽車體設計
10-3 比賽夾爪設計
10-4 競賽組決賽試題
Chapter 11 MARC 聯盟賽（需選購擴充包）
11-1 MARC 聯盟賽規則（2024 版本）
11-2 比賽車體設計
11-3 操作MJ2 手把
11-4 程式設計：手把操控夾爪
Chapter 12 WRO（World Robot Olympiad）國際奧林匹亞機器人競賽
12-1 賽事介紹
12-2 賽事主題
附錄
課後習題答案與解析
參考資料
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Quantum Geometry, Matrix Theory, and Gravity (1版)
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【簡介】
Building on mathematical structures familiar from quantum mechanics, this book provides an introduction to quantization in a broad context before developing a framework for quantum geometry in Matrix Theory and string theory. Taking a physics-oriented approach to quantum geometry, this framework helps explain the physics of Yang–Mills-type matrix models, leading to a quantum theory of space-time and matter. This novel framework is then applied to Matrix Theory, which is defined through distinguished maximally supersymmetric matrix models related to string theory. A mechanism for gravity is discussed in depth, which emerges as a quantum effect on quantum space-time within Matrix Theory. Using explicit examples and exercises, readers will develop a physical intuition for the mathematical concepts and mechanisms. It will benefit advanced students and researchers in theoretical and mathematical physics, and is a useful resource for physicists and mathematicians interested in the geometrical aspects of quantization in a broader context.
【目錄】
Preface
The trouble with spacetime
Quantum geometry and Matrix theory
Part I. Mathematical Background:
1. Differentiable manifolds
2. Lie groups and coadjoint orbits
Part II. Quantum Spaces and Geometry:
3. Quantization of symplectic manifolds
4. Quantum spaces and matrix geometry
5. Covariant quantum spaces
Part III. Noncommutative field theory and matrix models:
6. Noncommutative field theory
7. Yang–Mills matrix models and quantum spaces
8. Fuzzy extra dimensions
9. Geometry and dynamics in Yang–Mills matrix models
10. Higher-spin gauge theory on quantum spacetime
Part IV. Matrix Theory and Gravity:
11. Matrix theory: maximally supersymmetric matrix models
12. Gravity as a quantum effect on quantum spacetime
13. Matrix quantum mechanics and the BFSS model
Appendixes
References
Index.
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Introduction to Matrix Theory (2版)
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Linear algebra and matrix theory are among the most important and most frequently applied branches of mathematics. They are especially important in solving engineering and economic models, where either the model is assumed linear, or the nonlinear model is approximated by a linear model, and the resulting linear model is examined.
This book is mainly a textbook, that covers a one semester upper division course or a two semester lower division course on the subject.
The second edition will be an extended and modernized version of the first edition. We added some new theoretical topics and some new applications from fields other than economics. We also added more difficult exercises at the end of each chapter which require deep understanding of the theoretical issues. We also modernized some proofs in the theoretical discussions which give better overview of the study material. In preparing the manuscript we also corrected the typos and errors, so the second edition will be a corrected, extended and modernized new version of the first edition.
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Sample Chapter(s)
Preface
Chapter 1: Vectors and Matrices
Contents:
Vectors and Matrices
Vector Spaces and Inner-Product Spaces
Systems of Linear Equations, and Inverses of Matrices
Determinants
Linear Mappings and Matrices
Eigenvalues, Invariant Subspaces, Canonical Forms
Special Matrices
Elements of Matrix Analysis
Readership: Written primarily for undergraduate and graduate students studying engineering, economics and business; can also be used in courses offered by the mathematics department, or by any kind of engineering and social sciences; can also be used by researchers in mathematics, economics, engineering; in addition, high school special courses, and teacher training courses can employ this textbook.
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Matrix Analysis of Structures, SI Edition 3/E 2022 <Cengage> (3版)
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Matrix and Tensor Decompositions in Signal Processing, Volume 2
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The second volume will deal with a presentation of the main matrix and tensor decompositions and their properties of uniqueness, as well as very useful tensor networks for the analysis of massive data. Parametric estimation algorithms will be presented for the identification of the main tensor decompositions. After a brief historical review of the compressed sampling methods, an overview of the main methods of retrieving matrices and tensors with missing data will be performed under the low rank hypothesis. Illustrative examples will be provided.
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