基于压缩感知和稀疏优化的数学实验案例设计

摘要

将在信息论、图像处理、地球科学、光学成像、模式识别、无线通信、大气、地质等领域受到高度关注的压缩感知和稀疏优化引入数学实验课程。设计难度适中的实验案例并利用Matlab语言编程实现，既实现了教学与科研资源共享，又介绍了Matlab优化工具箱求解线性规划问题的方法，拓宽了学生的视野，丰富了数学实验课程的教学内容。%A mathematical experiment was presented on compressed sensing and sparse optimization,which are followed closely in information theory,image processing,earth science,optical imaging,pattern recognition,wireless communication,atmospheric,geological and other areas. The mathematical experiment was moderate in terms of difficulty and implemented in Matlab language. The design of this experiment included the resources of teaching and research,what′s more,the function of linear programming in Matlab was introduced,which broaden the horizons of students and enriched the content of mathematical experiment course.