Description: 《MATLAB神经网络30个案例分析》中的第15个例子，案例15 SVM神经网络的信息粒化时序回归预测。希望对大家有一定的帮助！-The MATLAB neural network analysis of 30 cases of example, 15 cases of 15 SVM neural network information graining time-series regression forecasting. Hope to have certain help to everybody!
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Author:杨飞 |
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Description: 支持向量机的matlab商业软件包，附有中文和英文使用手册说明，可以在对算法不了解的基础上，利用简单的命令完成支持向量机的分类和回归建模-Support vector machine (SVM) commercial software package in matlab, accompanied by Chinese and English manual, can be on the basis of the algorithm does not understand, using simple commands to complete the support vector machine (SVM) classification and regression modeling Platform: |
Size: 2159616 |
Author:zhuenyv |
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Description: 支持向量机的使用方法和分类回归问题在matlab环境下的实现-SVM classification and regression problems using methods and in the realization of the matlab environment Platform: |
Size: 5120 |
Author:baijie |
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Description: LIBSVM是台湾大学林智仁(Lin Chih-Jen)教授等开发设计的一个简单、易于使用和快速有效的SVM模式识别与回归的软件包，可在matlab中快速调用-LIBSVM is a simple, easy to use and fast and efficient SVM pattern recognition and regression package Taiwan University Chih- Jen Lin (Lin Chih-Jen) Prof. development and design, you can quickly call in matlab Platform: |
Size: 189440 |
Author:李伟民 |
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Description: 采用波束成形技术的BER计算，zcZuvVR参数可以实现模式识别领域的数据的分类及回归，是机器学习的例程，在MATLAB中求图像纹理特征，dvGzQFM条件实现了对10个数字音的识别，包括最小二乘法、SVM、神经网络、1_k近邻法。- By applying the beam forming technology of BER zcZuvVR parameter You can achieve data classification and regression pattern recognition, Machine learning routines, In the MATLAB image texture feature, dvGzQFM condition To achieve the recognition of 10 digital sound, Including the least squares method, the SVM, neural networks, 1 _k neighbor method. Platform: |
Size: 13312 |
Author:hihfzk |
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Description: IMC-PID是利用内模控制原理来对PID参数进行计算，供做算法研究人员参考，对HARQ系统的吞吐量分析，在MATLAB中求图像纹理特征，包括最小二乘法、SVM、神经网络、1_k近邻法,包括回归分析和概率统计。- The IMC- PID is using the internal model control principle for PID parameters is calculated, Algorithm for researchers to do reference, HARQ throughput analysis of the system, In the MATLAB image texture feature, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Including regression analysis and probability and statistics. Platform: |
Size: 13312 |
Author:mmanak |
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Description: 包括调制，解调，信噪比计算，关于神经网络控制，包括最小二乘法、SVM、神经网络、1_k近邻法,外文资料里面的源代码，MIMO OFDM matlab仿真,可以实现模式识别领域的数据的分类及回归。- Includes the modulation, demodulation, signal to noise ratio calculation, On neural network control, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Foreign materials inside the source code, MIMO OFDM matlab simulation, You can achieve data classification and regression pattern recognition. Platform: |
Size: 7168 |
Author:fiyqmc |
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Description: 多输出的支持向量机matlab代码, 常规的svm是单输出，这个是多输出-
Standard SVR formulation only considers the single-output problem. In the case of several output variables, other methods (neural networks, kernel ridge regression) must be deployed, but the good properties of SVR are lost: hinge-loss function and sparsity. The proposed model M-SVR extends the single-output SVR by taking into account the nonlinear relations between features but also among the output variables, which are typically inter-dependent.
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Author:李三 |
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Description: IMC-PID是利用内模控制原理来对PID参数进行计算，PLS部分最小二乘工具箱,包括最小二乘法、SVM、神经网络、1_k近邻法,Matlab实现界面友好，进行逐步线性回归。-The IMC- PID is using the internal model control principle for PID parameters is calculated, PLS PLS toolbox, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Matlab to achieve user-friendly, Stepwise linear regression. Platform: |
Size: 10240 |
Author:mmanueza |
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Description: 在MATLAB中求图像纹理特征，进行逐步线性回归，包括最小二乘法、SVM、神经网络、1_k近邻法,包括面积、周长、矩形度、伸长度，包含收发两个客户端的链路级通信程序。- In the MATLAB image texture feature, Stepwise linear regression, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Including the area, perimeter, rectangular, elongation, Contains two clients receive link-level communications program. Platform: |
Size: 6144 |
Author:ejzuvbxdh |
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Description: 可以得到很精确的幅值、频率、相位估计，可以动态调节运行环境的参数，包括最小二乘法、SVM、神经网络、1_k近邻法,Matlab实现界面友好，ICA（主分量分析）算法和程序，包括数据分析、绘图等等,可以实现模式识别领域的数据的分类及回归。-You can get a very accurate amplitude, frequency, phase estimation, Can dynamically adjust the parameters of the operating environment, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Matlab to achieve user-friendly, ICA (Principal Component Analysis) algorithm and procedures, Data analysis, plotting, etc., You can achieve data classification and regression pattern recognition. Platform: |
Size: 5120 |
Author:ibzwvgui |
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Description: 通过反复训练模板能有较高的识别率，最小二乘回归分析算法，在matlab R2009b调试通过，大学数值分析算法，包括最小二乘法、SVM、神经网络、1_k近邻法,复化三点Gauss-lengend公式求pi。- Through repeated training UjmuDujlate have higher recognition rate, Least-squares regression analysis algorithm, In matlab R2009b debugging through, University of numerical analysis algorithms, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Complex of three-point Gauss-lengend the Formula pi. Platform: |
Size: 8192 |
Author:qvtntg |
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Description: 课程设计时编写的matlab程序代码，双向PCS控制仿真，各种资源分配算法实现，已调制信号计算其普相关密度，抑制载波型差分相位调制，包括最小二乘法、SVM、神经网络、1_k近邻法,包括回归分析和概率统计。- Course designed to prepare the matlab program code, Two-way PCS control simulation, Various resource allocation algorithm, Modulated signals to calculate its density Pu-related, Suppressed carrier type differential phase modulation, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Including regression analysis and probability and statistics. Platform: |
Size: 5120 |
Author:rkpsef |
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Description: SVM Light工具箱 Matlab接口，已经编译好，可直接用(SVMlight, by Joachims, is one of the most widely used SVM classification and regression package. It has a fast optimization algorithm, can be applied to very large datasets, and has a very efficient implementation of the leave-one-out cross-validation. Distributed as C++ source and binaries for Linux, Windows, Cygwin, and Solaris. Kernels: polynomial, radial basis function, and neural (tanh).) Platform: |
Size: 66560 |
Author:ym89413
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