完整的大学数据结构大作业，杂志管理系统

可以上传照片，可以编辑生成杂志，可以对图片进行调整和排序以及书写目录

Jordan和Mitchell两位Machine learning大牛在Science 杂志综述长文——机器学习发展趋势和前景

详细的杂志订阅管理系统，由于c/c++课程设计

Endnote 杂志格式style 集合了几千套SCI杂志的模板，下载直接导入endnote，实数精品，科研论文必备。写文章，投杂志求己不求人。

好辛苦找到这个模板，超级合适写一篇学术论文。下载就能用 就能用 就能用！！！！！！！！！！！！！！！还很适合学习。写出来的论文超美，谁用谁造。latex坚定支持者。

大一课设，可登录查询添加删除等等操作，全部用C语言编写，适合入门学生，简单易懂，注释清楚，链表完成，简单易懂，注释清楚

使商家能方便地对杂志订阅信息进行增加、删除、修改等日常维护，并且能进行杂志订阅信息的查询，从而更全面地了解到杂志订阅相关信息。

这是一篇来自science杂志的论文，非常经典！介绍了测地距离在流行降维中的应用。 Scientists working with large volumes of high-dimensional data, such as global climate patterns, stellar spectra, or human gene distributions, regularly confront the problem of dimensionality reduction: Þnding meaningful low-dimensional structures hidden in their high-dimensional observations. The human brain confronts the same problem in everyday perception, extracting from its high-dimensional sensory inputsÑ30,000 auditory nerve Þbers or 106 optic nerve ÞbersÑa manageably small number of perceptually relevant features. Here we describe an approach to solving dimensionality reduction problems that uses easily measured local metric information to learn the underlying global geometry of a data set. Unlike classical techniques such as principal component analysis (PCA) and multidimensional scaling (MDS), our approach is capable of discovering the nonlinear degrees of freedom that underlie complex natural observations, such as human handwriting or images of a face under different viewing conditions. In contrast to previous algorithms for nonlinear dimensionality reduction, ours efÞciently computes a globally optimal solution, and, for an important class of data manifolds, is guaranteed to converge asymptotically to the true structure.

亚洲控制杂志期刊（asian journal of control），论文模板，欢迎下载！