计算方法》实验教学大纲

课程代码

045101691

课程名称

计算方法

英文名称

ComputationMethods

课程类别

专业基础课

选修课

课程性质

必修

选修

学时

总学时:48实验:8实习:0其他:0

学分

3.0

开课学期

6/4

开课单位

计算机科学与工程学院

适用专业

计算机科学与技术、网络工程、信息安全

授课语言

中文

先修课程

数学分析、线性代数与解析几何、高级语言程序设计

毕业要求(专业培养能力)

本课程对学生达到如下毕业要求的贡献:

  1. 工程知识:能够将数学、自然科学、工程基础和专业知识用于解决计算机复杂工程问题。

  2. 问题分析:能够应用数学、自然科学和工程科学的基本原理,识别、表达、并通过文献研究分析计算机复杂工程问题,以获得有效结论。

  3. 研究:能够基于科学原理并采用科学方法对与计算机相关复杂工程问题进行研究,包括设计实验、分析与解释数据、并通过信息综合得到合理有效的结论。

  4. 使用现代工具:能够针对与计算机相关复杂工程问题,开发、选择与使用恰当的技术、资源、现代工程工具和信息技术工具,包括对复杂工程问题的预测与模拟,并能够理解其局限性。

课程培养学生的能力(教学目标)

完成课程后,学生将具备以下能力:

  1. 掌握计算方法相关的基本概念[1/2/3]

  2. 掌握各种计算方法的基本思想、推导过程、计算步骤和编程实现[1/2/3/4]

  3. 掌握各种计算方法的误差估计和收敛性判断[1/2/3]

课程简介

本课程主要介绍使用计算机解决某些数学问题的近似方法,课程实用性较强,在科学研究、科学实验和工程技术中都有很多的应用。通过本课程的学习,使学生不仅要掌握计算方法的基本概念、各种计算方法的基本思想、推导过程、计算过程和在计算机上如何实现,而且也要掌握某些计算方法的误差估计和收敛性判断,为今后使用计算机解决实际问题打下良好的基础。

主要仪器设备与软件

PC机、编程环境(C++JavaPython等)

实验报告

每次实验需提交实验报告,实验报告的内容应包括实验目的及要求、实验环境、实验过程和实验小结等。

考核方式

本实验课程成绩将结合出勤、实验操作以及实验报告等进行综合评估,其中出勤占实验课程总评成绩的10%,实验操作占实验课程总评成绩的60%,实验报告占实验课程总评成绩的30%

教材、实验指导书及教学参考书目

实验指导书与参考书:

  1. 韩国强,林伟健等编著,数值分析,华南理工大学出版社,2005

  2. 李庆扬,王能超,易大义.数值分析(第5版).清华大学出版社,2008

  3. J.H.Mathews and K.D. Fink. Numerical Methods Using MATLAB (4thEdition). Photocopy, Beijing, China: Publishing House ofElectronics Industry, 2005

制定人及发布时间

何军辉,2019430


《课程名称》实验教学内容与学时分配

实验项目编号

实验项目名称

实验学时

实验内容提要

实验类型

实验要求

每组人数

主要仪器设备与软件


多项式插值与曲线拟合

2

  1. 拉格朗日插值和牛顿插值

  2. 最小二乘法曲线拟合

设计性

必做

1

PC机、编程环境


数值积分与线性方程组求解

2

  1. 自动选取步长梯形积分、龙贝格积分

  2. 高斯消去法、LU直接分解法、对称正定矩阵的平方根法

设计性

必做

1

PC机、编程环境


线性方程组和非线性方程迭代求解

2

  1. Jacobi迭代法和Seidel迭代求解线性方程组

  2. 对分法、松弛法和牛顿法求非线性方程根

设计性

必做

1

PC机、编程环境


特征值和特征向量/微分方程

2

  1. 幂法和雅可比方法求特征值和特征向量

  2. 龙格-库塔法求解微分方程

设计性

必做

1

PC机、编程环境


ComputationMethodsSyllabus

CourseCode

045101691

CourseTitle

ComputationMethods

CourseCategory

Specialty Basic Courses

ElectiveCourses

CourseNature

Compulsory Course

ElectiveCourse

ClassHours

Totalhours: 48 Experimental hours: 8 Practice hours: 0 Other hours:0

Credits

3.0

Semester

6/4

Institute

Schoolof Computer Science & Engineering

ProgramOriented

Computerscience and technology, Network engineering, Information security

TeachingLanguage

Chinese

Prerequisites

MathematicsAnalysis, Linear Algebra & Analytic Geometry, AdvancedLanguage Programming

StudentOutcomes (Special Training Ability)

Thiscourse contributes to the following graduation requirements forstudents:

  1. EngineeringKnowledge: An ability to apply knowledge of mathematics, science,engineering fundamentals and engineering specialization to thesolution of complex engineering problems.

  2. ProblemAnalysis: An ability to identify, formulate and analyze complexengineering problems, reaching to substantiated conclusions usingbasic principles of mathematics, science, and engineering.

  3. Research:An ability to conduct investigations of complex engineeringproblems based on scientific theories and adopting scientificmethods including design of experiments, analysis andinterpretation of data and synthesis of information to providevalid conclusions.

  4. ApplyingModern Tools: An ability to create, select and apply appropriatetechniques, resources, and modern engineering and IT tools,including prediction and modelling, to complex engineeringactivities, with an understanding of the limitations.

TeachingObjectives

Uponcompletion of the course, students will have the followingabilities:

  1. Masterthe basic concepts related to the computing method [1/2/3];

  2. Masterthe basic ideas of various computing methods, derivation process,calculation steps and programming implementation [1/2/3/4];

  3. Masterthe various methods of error estimation and convergence judgment[1/2/3].

CourseDescription

Thiscourse mainly introduces the approximate method of using computerto solve some mathematical problems. The course is practical andhas many applications in scientific research, scientificexperiment and engineering technology. Through the study of thiscourse, the students will not only master the basic concepts ofcomputing methods, the basic idea of various methods ofcalculation, derivation process, the calculation process andimplementation on computer, but also master some of thecalculation method of error estimation and convergence judgment.And it will lay a good foundation for the future use of computersto solve practical problems.

Instrumentsand Equipments

PC,programming environment (C ++, Java, Python, etc.)

ExperimentReport

Eachexperiment must submit an experimental report, the experimentalreport should include the contents of the experimentalrequirements, experimental environment, experimental process andexperimental summary.

Assessment

Theexperimental result will be evaluated with a comprehensiveassessment, including attendance, experimental operation andexperimental reports. Attendance accounts for 10% of the totalscore of the experimental course, experimental operations accountfor 60% of the total score of the experimental course, theexperimental reports account for 30% of the total score.

TeachingMaterials and Reference Books

ExperimentalGuidance and Reference:

  1. 韩国强,林伟健等编著,数值分析,华南理工大学出版社,2005

  2. 李庆扬,王能超,易大义.数值分析(第5版).清华大学出版社,2008

  3. J.H.Mathews and K.D. Fink. Numerical Methods Using MATLAB (4thEdition). Photocopy, Beijing, China: Publishing House ofElectronics Industry, 2005

Preparedby Whom and When

JunhuiHe, April 30, 2019

ComputationMethodsExperimentalTeaching Arrangements

No.

ExperimentItem

ClassHours

ContentSummary

Category

Requirements

Numberof StudentsEach Group

Instruments,Equipments and Software

1

PolynomialInterpolation and Curve Fitting

2

  1. Lagrangianinterpolation and Newton interpolation

  2. Leastsquare curve fitting

Design

Compulsory

1

PC,programming environment (C ++, Java, Python, etc.)

2

NumericalIntegral and Solution of Linear Equations

2

  1. Automaticallyselect the step length trapezoidal integral, Longberg integral

  2. Gaussianelimination method, LU direct decomposition method, symmetricpositive definite matrix square root method

Design

Compulsory

1

PC,programming environment (C ++, Java, Python, etc.)

3

SolvingLinear Equations and Nonlinear Equations

2

  1. Jacobiiterative method and Seidel iteration to solve linear equations

  2. Bisection,relaxation method and Newton method to find the nonlinearequation root

Design

Compulsory

1

PC,programming environment (C ++, Java, Python, etc.)

4

Eigenvalueand eigenvector / differential equation

2

  1. Powerlaw and Jacobian method for eigenvalues and eigenvectors

  2. Runge-Kuttamethod for solving differential equations

Design

Compulsory

1

PC,programming environment (C ++, Java, Python, etc.)