资源列表
feature-selection-master
- mRMR(最小冗余最大相关)算法，有说明有源码(mRMR (minimum redundancy maximum correlation))
压缩感知DOA估计方法
- 该方法通过压缩方法求积信号的到达角，为了获得更精确的DOA估计值，把字典建模为可自由调整的参数描述的模型，通过梯度学习的方法，不断更新字典的格点值。
Autonomous Vehicle Control
- matlab代码生成转向和速度（phi，v）命令，使自主车辆遵循预先定义的路径参考路径（x，y）(Matlab code to generate steering and speed (phi,v) command for an autonomous vehicle to follow a predefined path reference path (x,y))
6_2_VGG
- 用thensorflow实现对VGGNET深度卷积神经网络的建立。(The establishment of the VGGNET convolutional neural network is implemented with the thenthraceflow.)
tensorflow预测产品价格
- 使用tensorflow进行预测，通过市场销量等数据预测产品的价格
LSTM-prediction
- 通过改进RNN神经网络经典的LSTM模型预测交通流。(prediction traffic flow)
LSTM程序
- 基于LSTM的时间序列预测-原理-python代码(Prediction of time series based on LSTM - principles -python code)
基于神经网络的车牌识别
- 基于神经网络的车牌识别，在原有基础上增多了训练集，提高了识别的准确度(Vehicle license plate recognition based on neural network increases the training set and improves the accuracy of recognition.)
AcousticChannelSimulator
- 计算海洋声学 深海声道模型 射线声学方法(Computational ocean acoustic deep-sea channel model)
鸢尾花
- 封装KNN算法，了解IRIS数据集 分类鸢尾花数据集(Encapsulation of KNN algorithm to understand IRIS dataset classification iris dataset)
time-series-forecasting-keras-master
- 基于ARIMA模型和LSTM模型，提出一种高性能得时间序列预测算法(Based on ARIMA model and LSTM model, a high performance time series prediction algorithm is proposed.)
强化学习
- 基础的强化学习Q-learning算法，对初学者对Q-learning算法得理解比较有帮助，程序包括运行脚本，Q-learning算法脚本以及环境脚本。(Basic reinforcement learning Q-learning algorithm is helpful for beginners to understand Q-learning algorithm. Programs include running scr ipt, Q-learning algorithm scr ipt