数值逼近

学分：3学分

先修课程：实分析与微积分；向量、几何与线性代数；多元微积分与向量分析

课程简介和目标：

《数值逼近》课程通常是数学类专业的信息与计算科学专业的首门基础专业课程，它介绍数值逼近的方法和理论，主要内容包括函数的插值、和曲线拟合、最佳逼近、数值微分、数值积分和快速Fourier变换等．掌握好该课程的知识，运用所学知识在计算机上实现数值逼近，将具有开展数值逼近工作的一定的实际能力，也为学习微分方程数值解、积分方程数值解等后续基础、专业课程提供必要的知识支撑．

成绩评定方式：

评定：学期总评成绩（100％）

重评：补考卷面成绩（100％）

成绩评定要求出勤率

推荐教材：

蒋尔雄，赵风光，苏仰锋　编著，数值逼近，复旦大学出版社，2008.07。

Numerical Approximation

Credits: 3 Credits

Pre-requisite: Real Analysis & the Calculus; Vectors, Geometry & Linear Algebra; Multivariable & Vector Analysis

Description：

Generally speaking, numerical approximation is a first important professional course for students in the major of information and computational sciences. This course consists of interpolation, curve fitting, best approximation, numerical differential methods, numerical integration and fast Fourier transforms. To learn basic concepts and capture numerical methods, and to realized numerical methods in personal computers will benefit to pratical work in real life. This course is a basic tool for many courses, such as numerical differential equations, numerical solutions for integral equations and other professional courses.

Methods of Summative Assessment：

Assessment: Assessments done during semester (100%)

Reassessment: best of 3 hour resit examination (100%)

Attendance at tutorials is a required element of this module.

Recommended textbooks：

Jiang Erxiong, Zhao Fengguang and Su Yangfeng, Numerical Approximation, Fudan University Press, 2008.07.

Detailed Lecture Notes will be provided to students.