▍1. supervised
说明: 监督学习训练网络,可以运用到雷达信号处理中(Supervised learning training network can be used in radar signal processing)
说明: 监督学习训练网络,可以运用到雷达信号处理中(Supervised learning training network can be used in radar signal processing)
说明: 粒子算法,轨迹规划参考,适用于无人驾驶,紧急避障等(Particle algorithm, trajectory planning reference, suitable for unmanned driving, emergency obstacle avoidance, etc)
说明: 使用的RNN中的LSTM进行对28个英文字母的简单文本预测(Use LSTM in RNN to make simple text prediction for 28 English letters)
说明: 差分进化算法python实现 比较简单啊啊啊啊啊啊(Differential evolution algorithm)
说明: 线弹性断裂相场法,后续更新!!共同学习!!(elastic fracture phase field)
说明: MATLAB源程序代码分享:MATLAB实现组对象的整体几何变换(Matlab Source Code Sharing: Matlab Group object to achieve the overall geometric transformation)
说明: 负荷预测 可以修改数据集进行预测谢谢谢谢谢谢(prediction in power election)
说明: 图像识别 安全帽检测 安全帽识别 用于安全帽的检测任务(Image recognition helmet detection helmet recognition for helmet detection task)
说明: 计算长方形产生的重力异常,理论计算和具体的实现方法.(Calculation of gravity anomaly caused by rectangle)
说明: 剪切波代码实现 有Matlab和python两个版本 都是可以运行和跑通的(The implementation of shear wave code has two versions: MATLAB and python, which can run and run.)
使用iwr16xx雷达板进行人体摔倒检测(Fall detection, useTI iwr16xx board)
说明: 使用iwr16xx雷达板进行人体摔倒检测(Fall detection, useTI iwr16xx board)
本代码采用python语言编写的的一个LSTM时间序列来预测销量(This code uses a LSTM time series written in Python language to predict sales)
说明: 本代码采用python语言编写的的一个LSTM时间序列来预测销量(This code uses a LSTM time series written in Python language to predict sales)
隐马尔科夫模型是关于时序的概率模型,描述由一个隐藏的马尔科夫链随机生成不可观测的状态随机序列,再由各个状态生成一个观测而产生观测序列的过程。隐藏的马尔科夫链随机生成的状态的序列,称为状态序列;每个状态生成一个观测,而由此产生的观测的随机序列,称为观测序列。马尔科夫链由初始概率分布、状态转移概率分布以及观测概率分布确定(The hidden Markov model is a probabilistic model for time series. It describes the process of randomly generating unobservable state random sequences from a hidden Markov chain, and then generating an observation by each state to produce an observation sequence. A sequence of randomly generated states of hidden Markov chains, called a sequence of states; each state produces an observation, and the resulting random sequence of observations is called an observation sequence. Markov chain is determined by initial probability distribution, state transition probability distribution and observation probability distribution)
说明: 隐马尔科夫模型是关于时序的概率模型,描述由一个隐藏的马尔科夫链随机生成不可观测的状态随机序列,再由各个状态生成一个观测而产生观测序列的过程。隐藏的马尔科夫链随机生成的状态的序列,称为状态序列;每个状态生成一个观测,而由此产生的观测的随机序列,称为观测序列。马尔科夫链由初始概率分布、状态转移概率分布以及观测概率分布确定(The hidden Markov model is a probabilistic model for time series. It describes the process of randomly generating unobservable state random sequences from a hidden Markov chain, and then generating an observation by each state to produce an observation sequence. A sequence of randomly generated states of hidden Markov chains, called a sequence of states; each state produces an observation, and the resulting random sequence of observations is called an observation sequence. Markov chain is determined by initial probability distribution, state transition probability distribution and observation probability distribution)