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Haykin
Dan Simon, Training radial basis neural networks with the extended Kalman Filter, 2001. Article on RBF neural networks, with examples, source programs on Matlab
- 2009-12-17 19:46:03下载
- 积分：1
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lms
说明： matlab实现陷波器，采用的是LMS 算法实现，能将特定的正弦信号滤去(matlab notch filter realization using the LMS algorithm, the sinusoidal signal to a particular least squares)
- 2008-11-11 16:19:35下载
- 积分：1
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Optimization_Toolbox
Matlab官方文档：优化工具箱Optimization toolbox(Matlab official documents : Optimization Toolbox Optimization toolbox)
- 2006-05-26 11:58:13下载
- 积分：1
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RetrieveL2
In this i attached matlab code for image retrieval function by finding the distance between training and testing features and arrange it in according to ascending order.
- 2013-10-06 15:08:52下载
- 积分：1
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filter
说明： 高斯滤波器对图像的去噪效果,具有很好的效果。(denoise on filter of gaussian)
- 2011-03-10 10:24:01下载
- 积分：1
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matlabDesign
Analysis.and.Design.of.Control.System.Using.MATLAB外文经典书目(Analysis.and.Design.of.Control.System.Using.MATLAB language classic bibliography)
- 2013-02-05 16:22:49下载
- 积分：1
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Matlabwaveletsecond
《MATLAB工程应用书库：MATLAB小波分析（第2版）》以最新版MATLAB R2011a为平台编写。从信号处理的角度阐述小波分析的基本原理及其应用。(The MATLAB application stacks: MATLAB wavelet analysis (second edition))
- 2013-11-28 12:56:51下载
- 积分：1
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Face_Angle_Neural_net
说明： 基于matlab的编程实现神经网络BP算法实现数据的分类(matlab bp)
- 2010-04-27 12:12:30下载
- 积分：1
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decoder_BPML
置信传播(belief propagation,BP)算法的计算复杂度较高，且变量节点和校验节点间信息传递的信息可靠，但是迭代的实现，就最大似然算法来说，验证其提高译码性能的特点。
(Belief propagation (belief propagation, BP) higher computational complexity of the algorithm, and reliable information between variable nodes and check nodes of information transmission, but the realization of the iteration, the maximum likelihood algorithm, the verification of its improved decoding performance characteristics.)
- 2014-03-14 21:54:39下载
- 积分：1
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lib-mkl
Multiple kernel learning is a model to merge multiple kernels by linear combination. Mostly solving the models are slow due to explicit computation of kernels.
Here, we propose to approximate kernel map function explicitly in finite dimensional space. Then, we use dual coordinate descent to solve the SVM. By storing the solutions in primal, we do not have to compute the kernel explicitly. A group lasso regularization on kernel weights is solved with SVM alternatingly.
This is a side-project in my research projects with Dr. Yi-Ren Yeh and Dr. Frank Wang in Academia Sinica.
- 2013-03-19 01:13:45下载
- 积分：1
