资源简介
This textbook introduces sparse and redundant representations with a focus on applications in signal and image processing. The theoretical and numerical foundations are tackled before the applications are discussed. Mathematical modeling for signal sources is discussed along with how to use the proper model for tasks such as denoising, restoration, separation, interpolation and extrapolation, compression, sampling, analysis and synthesis, detection, recognition, and more. The presentation is elegant and engaging. Sparse and Red undant Representations is intended for graduate students in applied mathematics and electrical engineering, as well as applied mathematicians, engineers, and researchers who are active in the fields of signal and image processing.
代码片段和文件信息
相关资源
- 稀疏表示和协同编码哪个对人脸识别
- 基于稀疏表示的图像去噪算法
- 压缩感知基础资料两篇论文,一个p
- 压缩感知重建算法——GPSR算法
- 基于稀疏表示的图像超分辨方法研究
- KSVD稀疏表示字典训练程序
- 压缩感知测量矩阵构造方法的研究
- 压缩感知方法实现SAR三维成像
- GPSR 梯度投影法
- Wavelet_CoSaMP
- CASSI基于压缩感知的光谱成像源代码
- 压缩感知-单像素相机-RICE大学的源代
- 压缩感知原理及应用完整版
- 稀疏表示算法
- 经典的介绍压缩感知原理的入门书籍
- 压缩感知中用OMP算法重构视频序列程
- Godec 稀疏表示与低秩表示的结合
- 压缩感知各种重构算法经典论文合集
- A Mathematical Introduction to Compressive Sen
- 关于稀疏表示的代码 可用
- 高维数据降维算法综述_景明利.pdf
- 压缩感知二维OMP
- 压缩感知文献综述
- 论文研究-基于SVD分解的二维多任务压
- 对压缩感知做出全面介绍通俗易懂
- 压缩感知BP LASSO OMP STOMP算法内含完整
- DCS_SOMP分布式压缩感知
- 压缩感知英文综述
- 1—bit压缩感知重构算法BITH
- 信号DCT字典稀疏表示
评论
共有 条评论