资源列表
ReinforcementLearning
- 利用MATLAB实现Q学习，简单易懂，欢迎大家下载(Using MATLAB to implement Q learning)
TspTS
- 采用禁忌搜索算法求解旅行商问题，欢迎下载(Traveling salesman problem is solved by Tabu Search Algorithm)
台湾大学李宏毅教授深度学习
- 学习深度学习的经典课件，来自台湾大学李宏毅教授(Learn the classic courseware for deep learning, Professor Li Hongyi from National Taiwan University)
WindowsFormsApplication5
- 压缩文件测试工具，可以将选中的路径生成压缩包(Zip file testing tool, you can select the path to generate compressed packets)
MATLAB神经网络43个案例分析
- MATLAB处理神经网络的43个案例，推荐学习(MATLAB neural network processing 43 cases, it is recommended to learn)
PIDAdjusting
- 采用遗传算法进行管道调节阀参数整定，欢迎下载(Genetic algorithm is used to adjust the parameters of pipeline control valve)
rtkpost
- 通过广播星历和精密星历实现GNSS数据的快速解算(The fast calculation of GNSS data is realized by broadcast ephemeris and precise ephemeris)
ColorC
- Color Corellologram in MATLAB
离散结构ppt
- 括号匹配，数据结构中比较重要 的栈的利用，数据结构中比较重要 的栈的利用。(Parentheses matching, data structure in the more important use of the stack, the data structure of the more important use of the stack.)
KNN
- 最近邻学习算法，Python实现，最近邻规则分类(steps: In order to determine the unknown instance categories, with examples of all known categories as reference Parameter selection of K The calculation examples and all known examples of the unknown distance Choose the
01DTree
- 步骤： 为了判断未知实例的类别，以所有已知类别的实例作为参照 选择参数K 计算未知实例与所有已知实例的距离 选择最近K个已知实例 根据少数服从多数的投票法则(majority-voting)，让未知实例归类为K个最邻近样本中最多数的类别(steps: In order to determine the unknown instance categories, with examples of all known categories
数据结构习题算法
- 数据结构课后习题相关算法完整源代码，陆续后面会上传更多源代码，供大家参考交流。(Data structure after-school exercises related algorithms complete source code)