搜索资源列表
CEEMDAN_V00
- A COMPLETE ENSEMBLE EMPIRICAL MODE DECOMPOSITION WITH ADAPTIVE NOISE
ANO_FLY
- 四旋翼利用无线通信，集合卡尔曼滤波和PID和四元数算法，稳定飞行-Four rotors use CAN communication, ensemble Kalman filter and PID and quaternion algorithm, and stable flight
robustlssvm
- 鲁棒最小二乘双支持向量机集成学习算法，对于初学者的理解应用特别好用-Robust least squares double support vector machine ensemble learning algorithm for beginners to understand the application of special good use
2D-Lattice-Percolation
- 2D-Lattice-Percolation,and ensemble average
eemd0
- 集合经验模式分解：噪声辅助数据分析方法-Ensemble Empirical Mode Decomposition: A noise-assisted data analysis method
Ensemble-Learning
- 集成学习将若干基分类器的预测结果进行综合，具体包括Bagging算法和AdaBoost算法；还有随机森林算法，利用多棵树对样本进行训练并预测的一种分类器-Integrated learning integrates the prediction results of several base classifiers, including Bagging algorithm and AdaBoost algorithm and random forest algorithm, using a t
sentiment_analysis_on_online_customer_reviews
- The project is to determine how much a particular factor influences on the helpfulness of a review. We extracted features like polarity, rating, average word length, helpfulness ratio the collected amazon data. We used gradient boosting classifie
ensemble
- 对分类错误的样本所对应权重进行累加得到加权误分类率, 这里我们是基于权重向量而不是其他的错误计算指标来评价分类器的-The weighting of the samples with the wrong classification is weighted by the weighted error rate, where we uate the classifier based on the weight vector rather than the other erroneous met
demo3
- 在demo中，用EKF和有噪声的EKF训练非线性、非平稳数据。-In this demo, I use the EKF and EKF with noise adaptation to train a neural network with data generated a nonlinear, non-stationary state space model. Adaptation is done by matching the innovations ensemble covariance
Ensemble_Toolbox
- ensemble tool box from mathwork
ising
- The Ising model, developed by Dr. Ernst Ising is used for modelling ferromagnetic and anti-ferromagnetic materials I The model represents a lattice occupied by atoms which can each have dipole moments or spins I The model predicts a second order
enkf-matlab
- 简明全面地实现了集合卡尔曼滤波资料同化的方法，缺乏主程序，需要自己调试，英文注释。(The method of data assimilation for ensemble Calman filtering is simple and comprehensive. It lacks the main program and needs to debug itself.)
56163048eemd
- 总体经验模式分解 信号处理方面的应用 经验模态分解的进化版(ensemble empirical mode decomposition)
基于NARX神经网络的轨道垂向不平顺估计_王贵
- 摘要:应用白噪声聚类经验模型分解方法(EEMD, Ensemble EMD)，进行轨道一车辆系统的时频分析， 分析钢轨不平顺的波长一幅值分布及短波不平顺的分布特点。通过理论推导，得到垂向钢轨不平顺与车体垂向 加速度之间的转移函数，并由简化模型仿真结果与实验数据对比分析得出二者的相关系数在0. 8以上，表明仿 真结果与实验数据非常吻合。利用简化模型进行数值仿真，所需复数乘法次数为N(21ogN+ 1)，满足实时仿真 的需要。实例所测钢轨不平顺和车体加速度的相关性分析结果表明，对加速度数据
CNTK
- 在深度的重要性的驱使下，出现了一个新的问题：训练一个更好的网络是否和堆叠更多的层一样简单呢？解决这一问题的障碍便是困扰人们很久的梯度消失/梯度爆炸，这从一开始便阻碍了模型的收敛。归一初始化（normalized initialization）和中间归一化（intermediate normalization）在很大程度上解决了这一问题，它使得数十层的网络在反向传播的随机梯度下降（SGD）上能够收敛。 当深层网络能够收敛时，一个退化问题又出现了：随着网络深度的增加，准确率达到饱和（不足为奇）然后迅
boosting_demo
- boosting算法用于集成学习，包含多种弱分类器(Boosting algorithm is used for ensemble learning, and it contains many weak classifiers)
xgboost
- 集成学习，它是二阶求导，速度快，可实现并行计算(Ensemble learning, which is a two order derivative, is fast and can be implemented in parallel computing)
eemdtool
- 实测可用，EEMD是Ensemble Empirical Mode Decomposition的缩写，中文是集合经验模态分解，是针对EMD方法的不足，提出了一种噪声辅助数据分析方法。EEMD分解原理是当附加的白噪声均匀分布在整个时频空间时，该时频空间就由滤波器组分割成的不同尺度成分组成。(Complete program, measured available.EEMD is an acronym for Ensemble Empirical Mode Decomposition. Chines
ceemdan
- 自适应白噪声的完整经验模态分解，在信号处理领域有强大的分解能力，是改进的HHT的一种方法，适合对非线性、非平稳信号进行分解。(Complete Ensemble Empirical Mode Decomposition with Adaptive Noise It has powerful decomposition ability in the field of signal processing which is an improved method of HHT It is sui
EMD with adaptive noise
- 以适应噪音为模型的经验模式分解，添加了一个特殊的噪声分解，获得每个阶段的模式。由此产生的分解完全可以忽略不计的误差。(Ensemble Empirical Mode decomposition with adaptive noise)