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斯坦福大学开放课程 : 傅立叶变换及应用 Open Stanford Course : The Fourier Transform and Its Applic

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    资源信息:



    中文名


    : 斯坦福大学开放课程 : 傅立叶变换及应用


    英文名


    : Open Stanford Course : The Fourier Transform and Its Applications


    资源格式


    : MP4


    课程类型


    : 数学


    学校


    : Stanford University 斯坦福大学


    主讲人


    : Brad Osgood


    版本


    : 开放式课程 更新完毕


    发行日期


    : 2009年


    地区


    : 美国


    对白语言


    : 英语


    文字语言


    : 英文


    概述


    :



    资源简介: Stanford大学开放课程: The Fourier Transform and Its Applications 课程代号: EE261 主讲: Brad Osgood 官网链接: https://ccnet.stanford.edu/ee261/ 斯坦福大学开放课程: 傅立叶变换及应用 该资源包括1-30课全部课程录像,并有428页Lecture Notes for EE 261The Fourier Transform and its Applications, formula sheet的pdf文档 课程简介: Course Coordinator: Brad Osgood Course Description: The Fourier transform is ubiquitous in engineering and science and this course is appropriate for students from across the engineering and science disciplines. The course emphasizes both mathematical know-how and applications. The goals for the course are to gain a facility with using the Fourier transform, both specific techniques and general principles, and learning to recognize when, why, and how it is used. Together with a great variety, the subject also has a great coherence, and the hope is students come to appreciate both. Topics include: The Fourier transform as a tool for solving physical problems. Fourier series, the Fourier transform of continuous and discrete signals and its properties. The Dirac delta, distributions, and generalized transforms. Convolutions and correlations and applications; probability distributions, sampling theory, filters, and analysis of linear systems. The discrete Fourier transform and the FFT algorithm. Multidimensional Fourier transform and use in imaging. Further applications to optics, crystallography. Emphasis is on relating the theoretical principles to solving practical engineering and science problems.




    目录


    : 课程内容预览: Topics include: 1. Periodicity and Fourier series 2. The Fourier transform and its basic properties 3. Convolution and its applications 4. Distributions and their Fourier transforms 5. Sampling and interpolation 6. Linear systems 7. The discrete Fourier transform 8. Higher dimensional Fourier transforms and applications


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