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資訊科學數學 1 : Introduction to Info Math 陳光琦助理教授 (Kuang-Chi Chen)

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Presentation on theme: "資訊科學數學 1 : Introduction to Info Math 陳光琦助理教授 (Kuang-Chi Chen)"— Presentation transcript:

1 資訊科學數學 1 : Introduction to Info Math 陳光琦助理教授 (Kuang-Chi Chen) chichen6@mail.tcu.edu.tw

2 Textbooks 1. Linear Algebra, S.H. Friedberg, A.J. Insel, and L.E. Spence, 4 th ed., Prentice Hall, 2003. 2. Discrete and Combinatorial Mathematics: An Applied Introduction, 5/e, R.P. Grimaldi, Addison-Wesley, 2004. References: References: 1. Elementary Linear Algebra, L.E. Spence, A.J. Insel, and S.H. Friedberg, Prentice-Hall, 2000. 2. Discrete Mathematics and Its Applications, K.H. Rosen, 6 th ed., McGraw Hill, 歐亞代理. 3. Introductory Combinatorics, R.A. Brualdi, 4 th ed., Pearson Prentice Hall, 2004. 4. Fundamentals of Numerical Computing, L.F. Shampine, R.C. Allen Jr., and S. Pruess.

3 Schedule-1 1 Introduction to Info Math 2 Basic Rules of Counting 3 Logic 4 Sets Theory 5 Mathematical Induction 6 Principles of Inclusion and Exclusion 7 Relations and Functions 8 Vector Spaces 9 -- Midterm exam --

4 Schedule-2 10 Linear Transformations and Matrices 11 Elementary Matrix Operations and Systems of Linear Equations 12 Determinants 13 Diagonalization 14 Inner Product Spaces 15 The Singular Value Decomposition 16 Projectors and QR Factorization 17 Least Squares Problems 18 Oral Presentation or -- Final --

5 Evaluation Assignment: Homework 20%, Assignment: Homework 20%, Oral presentation 10%, Oral presentation 10%, Attendance 10%; Attendance 10%; Exam: Midterm 30%, Exam: Midterm 30%, Final 30%. Final 30%.

6 What Is Informatics Math? This course is an elementary discrete mathematics and linear algebra course oriented towards applications in computer science and engineering. This course is an elementary discrete mathematics and linear algebra course oriented towards applications in computer science and engineering. Topics covered include: logic notation, induction, sets and relations, vector spaces, matrix and linear equations, determinants, diagonalization, and inner product spaces. Topics covered include: logic notation, induction, sets and relations, vector spaces, matrix and linear equations, determinants, diagonalization, and inner product spaces.

7 Why We Need Informatics Math? 學生背景廣,一些在資訊科學中會用到的 數學基本模式,對爾後做研究有幫助。 學生背景廣,一些在資訊科學中會用到的 數學基本模式,對爾後做研究有幫助。 資訊與數學的關係 資訊與數學的關係 了解觀念與理論 了解觀念與理論 靈活應用 靈活應用 加強分析 加強分析

8 Course Objectives Students will be able to explain and apply the basic methods of discrete (noncontinuous) mathematics in Computer Science, using analytic and combinatorial methods in subsequent courses in the design and analysis of algorithms, computability theory, software engineering, and computer systems. Students will be able to explain and apply the basic methods of discrete (noncontinuous) mathematics in Computer Science, using analytic and combinatorial methods in subsequent courses in the design and analysis of algorithms, computability theory, software engineering, and computer systems. In particular, students will be able to: Using a basic subject on matrix theory and linear algebra. in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices. Using a basic subject on matrix theory and linear algebra. in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices.

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