Helicopter Pilot Training Mathematics Matrix Model and Demand Calculation 直升机飞行学员培训数学模型与需求预测
After the covariance matrix of the multi-channel data was obtained by the known training samples, the matrix was transformed into multidimension feature vectors as the input of the SVM and the weight vector was computed by training SVM. 从已知训练样本得到多通道数据的协方差矩阵,将得到的矩阵转化为SVM的输入多维特征向量,并训练SVM而获得权向量。
A MSET estimation method is presented based on the actual in-orbit state telemetry obtained data. And the data standardization process, training data selection, memory matrix structure and the nonlinear operator selection and optimization of MSET implementation technologies are given respectively. 提出了基于在轨遥测数据的MSET状态估计的方法,分别研究了数据正规化处理、训练数据选取、记忆矩阵构造和非线性算子选取及优化等MSET实现技术。
Therefore, selecting a training set is important for constructing score matrix and optimizing alignment. 因此训练集的选取对于打分矩阵的构建及其比对效果很关键。
To give a solution for multi-corner judging, new training algorithm for the construction of connection matrix between hidden and output layer of forward neural network trained is presented. 为解决数据的多类别判定问题,给出了新的角分类神经网络隐层与输出层之间连接矩阵的学习算法。