资源列表
mnist.pkl
- mnist数据集，手写体识别，可以应用于深度学习的测试数据-mnist dataset, used for handwriting recognize
FOA-algorithm-
- FOA是一种较新的只能算法，该算法具有较强的搜索能力，局部搜索能力较强，在连续问题和离散问题上都有很多的应用-FOA is a newer only algorithm, the algorithm has a strong search ability, strong local search ability, continuous problems and discrete problems have a lot of applications
neuralnet
- 收集的神经网络应用相关的文献，需要的同学拿去参考吧-Collection of neural network application related literature, the students need to take reference it
BPNN
- BPNN（BP NaturalNetwrok） 是一个构造BP神经网络的C++程序，可以手动设置神经网络隐含层的层数，输入层和输出层的节点数-BPNN（BP NaturalNetwrok）
K-NN等算法实现作业1
- CS231n课后作业的官方习题答案，运行环境为Python2，有需要的同学可以自取(The official CS231n homework exercise answers, the operating environment for the Python2, students need to pick up)
SGALAB1003beta5008_agriculture
- 带有模糊逻辑控制的多目标遗传算法,包括19个m文件和9个说明文档-Multi-objective genetic algorithm with fuzzy logic control，which include nineteen .m documents and nine guiding documents
人工智能原理
- 人工智能 第1章 绪论 第2章 刺激响应agent 第3章 神经网络 第4章 机器进化 第5章 状态机 。。。。。。 共25章(Artificial intelligence Chapter 1 Introduction Chapter 2 Stimulus Response Agent Chapter 3 Neural Network Chapter 4 Machine Evolution Chapter 5 State Machines ...
卷积网络matlab实现
- 用卷积神经网络（CNN）进行人脸识别，matlab编程，可用。(Convolutional neural network (CNN) is used for face recognition, and MATLAB programming is available.)
_Shunting-model
- 一个用LABVIEW 编写的机器人路径，追踪的程序使用到了SHUNTING 模型-SHUNTING MODEL IN ANN FOR MOBILE ROBOT
InertialNavigation
- 捷联导航相关知识，陀螺，及速度及惯性敏感器件和测试、补偿标定技术以及捷联系统算法的相关知识-Strapdown navigation knowledge, gyro, and speed and inertia-sensitive devices and tests, calibration and compensation algorithms SINS knowledge
Algorithm-1
- 演算法的基礎書籍,對於資訊工程或者電機工程相關的學生或者研究生有莫大助益-Algorithm is based on books, for information related to engineering or electrical engineering or graduate students of great help
autofaceV5.0
- 自动人脸检测识别系统V5.0是一套集图象处理、人脸检测和人脸识别以及人脸图像数据库管理于一体的完整人脸识别系统。-Automatic Face Detection and Recognition System V5.0 is a set of image processing, face detection and face recognition and human face image database management in one complete face recognition