资源列表
Artificial-Intelligence
- 《人工智能哲学》收集了人工智能研究领域著名学者的15篇代表性论文，这些论文为计算机科学的发展和人工智能哲学的建立做出了开创性的贡献。人工智能哲学是伴随现代信息理论和计算机技术发展起来的一个哲学分支。-" Artificial Intelligence philosophy" a collection of 15 papers representative of artificial intelligence research famous scholars, these pap
MINIST
- mnist库上 应用DBN网络 DBN使用RBM结构，半监督网络，逐层训练(Application on the DBN network)
PCANet_demo
- 一种简单的神经网络实现方式。PCANet-A simple neural network implementations. PCANet
nn_code
- 使用Python实现的一些简单神经网络算法，实现的神经网络包括BP,CNN,RNN,LSTM等，主要是理解这些神经网络的算法原理，并附有mnist数字识别例子。(neural network,include BP,CNN,RNN,LSTM.)
ICESatProcessor
- this program is for icesat processing
opmenrtifipuec
- As the rapid development of artificial intelligence technology,computer technology, electronic technology and signal processing，robot technology has made tremendous progress in recent years and the applications of the robot technology is also ver
AutoEncoder
- 最先提出深度学习算法hinton的自动编码器matlab代码，内容是：利用多层rbm进行自动编码的多层特征训练，然后使用梯度算法进行fine turn。可以进行特征提取，也可以进行分类。压缩包里已带有训练用签字图片数据。相应算法说明可以查看hinton于2006年发表在 science的文章-First proposed deep learning algorithm hinton automatic encoder matlab code that reads: multilayer r
Digit-Recognizer
- 在matlab平台上的数字识别，使用了几百个数字样本进行训练测试(digital recognition in matlab)
改进的GA优化BP
- 改进的遗传算法优化的BP神经网络，用于电厂数据的异常检测和故障诊断，已验证有效性。(The improved genetic algorithm optimized BP neural network has been validated for power plant data anomaly detection and fault diagnosis.)
零速校正原版
- 利用零速检测检测零速时刻然后进行零速校正进行行人导航(Zero speed detection is used to detect the zero speed moment, and then zero velocity correction is used for pedestrian guidance)
force signal hexapod
- 对力传感器测量到的力信号进行滤波，并得到更平滑的曲线，更清晰的显示数据走势，可用于各种带有噪声的信号绘图处理(The force signal is filtered by force sensor, and smoother curve is obtained. It shows the trend of data more clearly, and can be used in various signal drawing processing)
tensorflow-master
- 这一个压缩文件里包含了tensorflow一书中包含的一些程序片段的代码，希望对深度学习及对tensorflow感兴趣的初学者有用(This zip file consist of the codes of the programs in the book of Tensorflow. Hope it is useful to the leaner or starter of deep learning and tensorflow.)