Description: 小数据量法求混沌吸引子最大Lyapunov指数的Matlab程序，参考文献：张家树.混沌时间序列的Volterra自适应预测.物理学报.2000.03-small data method for chaotic attractor largest Lyapunov exponent of Matlab procedures References : Zhang Shu. The chaotic time series Volterra adaptive prediction. Physics reported .2000.03 Platform: |
Size: 8799 |
Author:江维 |
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Description: 基于Volterra滤波器混沌时间序列多步预测
作者：陆振波，海军工程大学
欢迎同行来信交流与合作，更多文章与程序下载请访问我的个人主页
电子邮件：luzhenbo@sina.com
个人主页：luzhenbo.88uu.com.cn
参考文献：
1、张家树.混沌时间序列的Volterra自适应预测.物理学报.2000.03
2、Scott C.Douglas, Teresa H.-Y. Meng, Normalized Data Nonlinearities for LMS Adaptation. IEEE Trans.Sign.Proc. Vol.42 1994
文件说明：
1、original_MultiStepPred_main.m 程序主文件,直接运行此文件即可
2、original_train.m 训练函数
3、original_test.m 测试函数
4、LorenzData.dll 产生Lorenz离散序列
5、normalize_1.m 归一化
6、PhaSpaRecon.m 相空间重构
7、PhaSpa2VoltCoef.dll 构造 Volterra 自适应 FIR 滤波器的输入信号矢量 Un
8、TrainTestSample_2.m 将特征矩阵前 train_num 个为训练样本，其余为测试样本
9、FIR_NLMS.dll NLMS自适应算法-based Volterra filters chaotic time series multi-step forecast Author : bo, the Navy Engineering from the University of peer welcome exchanges and cooperation, more and download articles please visit my personal web page e-mail : luzhenbo@sina.com WEBSITE : luzhenbo.88uu.com.cn References : 1, and Zhang Shu. the chaotic time series Volterra adaptive prediction. physics reported .2000.03 2, Scott C. Douglas, H.-Y. Teresa Meng, Normalized Data for LMS Adaptation Nonlinearities. IEEE Trans.Sign.Proc . Timing 1994 document : 1, original_MultiStepPred_main.m procedures master file directly run this document can be 2, 3 original_train.m training function, the function tests original_test.m 4, LorenzData.dll have Lorenz five discrete sequence, a normalize_1.m naturalization of six, PhaSpaRecon.m Platform: |
Size: 11847 |
Author:陆振波 |
Hits:
Description: 小数据量法求混沌吸引子最大Lyapunov指数的Matlab程序，参考文献：张家树.混沌时间序列的Volterra自适应预测.物理学报.2000.03-small data method for chaotic attractor largest Lyapunov exponent of Matlab procedures References : Zhang Shu. The chaotic time series Volterra adaptive prediction. Physics reported .2000.03 Platform: |
Size: 8192 |
Author:江维 |
Hits:
Description: 基于Volterra滤波器混沌时间序列多步预测
作者：陆振波，海军工程大学
欢迎同行来信交流与合作，更多文章与程序下载请访问我的个人主页
电子邮件：luzhenbo@sina.com
个人主页：luzhenbo.88uu.com.cn
参考文献：
1、张家树.混沌时间序列的Volterra自适应预测.物理学报.2000.03
2、Scott C.Douglas, Teresa H.-Y. Meng, Normalized Data Nonlinearities for LMS Adaptation. IEEE Trans.Sign.Proc. Vol.42 1994
文件说明：
1、original_MultiStepPred_main.m 程序主文件,直接运行此文件即可
2、original_train.m 训练函数
3、original_test.m 测试函数
4、LorenzData.dll 产生Lorenz离散序列
5、normalize_1.m 归一化
6、PhaSpaRecon.m 相空间重构
7、PhaSpa2VoltCoef.dll 构造 Volterra 自适应 FIR 滤波器的输入信号矢量 Un
8、TrainTestSample_2.m 将特征矩阵前 train_num 个为训练样本，其余为测试样本
9、FIR_NLMS.dll NLMS自适应算法-based Volterra filters chaotic time series multi-step forecast Author : bo, the Navy Engineering from the University of peer welcome exchanges and cooperation, more and download articles please visit my personal web page e-mail : luzhenbo@sina.com WEBSITE : luzhenbo.88uu.com.cn References : 1, and Zhang Shu. the chaotic time series Volterra adaptive prediction. physics reported .2000.03 2, Scott C. Douglas, H.-Y. Teresa Meng, Normalized Data for LMS Adaptation Nonlinearities. IEEE Trans.Sign.Proc . Timing 1994 document : 1, original_MultiStepPred_main.m procedures master file directly run this document can be 2, 3 original_train.m training function, the function tests original_test.m 4, LorenzData.dll have Lorenz five discrete sequence, a normalize_1.m naturalization of six, PhaSpaRecon.m Platform: |
Size: 11264 |
Author:陆振波 |
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Description:
利用线性神经网络进行自适应预测
利用函数adapt对线性网络进行自适应训练，在线修正网络的权值和阈值，这样对于时变信号，网络就可以及时跟踪其变化，即可对时变信号序列进行预测。
-linear adaptive neural network prediction using linear function adapt to the network adaptive training , the online network that the weights and thresholds, so for the time-varying signal, the network can track changes in a timely manner. will be the time-varying signal sequence forecast. Platform: |
Size: 3072 |
Author:mamin |
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Description: 利用adapt函数对自适应滤波网络对时变正弦信号进行自适应预测。-Adapt the use of adaptive filtering function network for time-varying sinusoidal signal adaptive prediction. Platform: |
Size: 1024 |
Author:qiulan |
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Description: 为了选择神经网络的最好结构以及增强模型的推广能力，提出一种自适应支持向量回归神经网络(SVR—NN)。SVR—NN 用支持向量回归(SVR)方法获得网络的初始结构和权值， 白适应地生
成网络隐层结点，然后用基于退火过程的鲁棒学习算法更新网络结点疹教和权 主。 SVR—NN有很
好的收敛性和鲁棒性，能抑制由于数据异常和参数选择不当所导致的“过拟合，’现象。将SVR—NN
应用到时间序列预测上。结果表明，SVR．NN预测模型能精确地预测混沌时间序列，具有很好的
理论和应用价值。-Abstract：To select the‘best’structure of the neural networks and enhance the generalization ability of models．a support
vector regression neural networks fSVR-NN)was proposed．Firstly，support vector regression approach was applied to
determine initial structure and initial weights of SVR．NN SO that the number of hidden layer nodes can be constructed
adaptively based on support vectors．Furthermore，an annealing robust learning algorithm was further presented to fine
tune the hidden node parameters and weights of SVR一ⅣM The adaptive SVR．NN has faSt convergence speed and robust
capability．and it can also suppress the ‘orerfitting’phenomena when the train data ncludes outliers．The adaptive
SVR．NN was then applied to time series prediction．Experimental results show that the adaptive SVR．ⅣⅣ can accurately
predict chaotic time series，and it iS valuable in both theory and application aspects． Platform: |
Size: 316416 |
Author:11 |
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Description: MATLAB codes for adaptive filtering using least mean square, nominal LMS and Wiener filter using forward linear prediction and backward linear prediction. Platform: |
Size: 176128 |
Author:MHQ
|
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Search - Adaptive prediction