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Bayesian衰退和分类模形
- 这个软件支持Bayesian衰退和分类模形，它基于神经系统网络和Gaussian作用。它也包括一些根本的程序实现有限和无限混合的模型。-software support this recession and Bayesian classification pattern, It is based on neural network and Gaussian role. It also includes some of the procedures to achieve limited and u
blindimagerecover
- 提出一种新的算法：逆主元法，利用高斯点扩展函数的特性，在径向基神经网络的模型下，对图像进行盲目复原。-a new algorithm : inverse main element method using Gaussian point spread function of the characteristics the RBF neural network model, the image blind rehabilitation.
pcnnlvbo
- 一个基于脉冲耦合神经网络的高斯噪声滤波程序，包括源码和实验结果-pulse coupling based on a neural network Gaussian noise filtering procedures, including source and experimental results
sasdw.rar
- 现有数字信号自动调制识别方法大多只适用于无记忆信号，如PSK、ASK、FSK信号等。将有记忆 信号(MSK信号)和无记忆信号一起考虑，提出了一种改进的数字信号自动识别方法。该方法采用信号的瞬时统 计量作为特征参数，采用多层神经网络作为分类器。计算机仿真表明：当噪声采用高斯白噪声，并且信噪比大于 l5 dB时，识别率高于96％ ；当信噪比不低于l0 dB时，识别率不低于90％。,Existing digital signal automatic modulation recognition
Estimate_Y
- 神经网络 高斯分布 最大后验估计 最大似然估计-Neural network Gaussian maximum a posteriori estimate maximum likelihood estimate
textureclassfication
- 提出了一种基于函数联接的感知器神经网络的纹理分类方法.它采用高斯2马尔柯夫随机场模型(GM RF)对纹理进行描述,模型参数即为纹理特征,参数估计采用最小平方误差方法获得.将估计参数作为表达纹理的特征向量,用感知器网络对特征进行分类,并且采用函数联接的方式解决线性不可分问题.对纹理图象进行的实验表明,采用这种方法能够提高学习速度,简化计算过程,并取得较好的纹理分类效果. -Based on the function connected perceptron neural network tex
Gaussian_Mixture_Models_and_Probabilistic_Decisio
- very good Gaussian Mixture Models and Probabilistic Decision-Based Neural Networks for Pattern Classification - A Comparative Study document -very good Gaussian Mixture Models and Probabilistic Decision-Based Neural Networks for Pattern Classificatio
hmmbox_4_1
- the newer version from HMMbox 3.2 Matlab toolbox for Variational estimation Hidden Markov Models. (Adapted from Hidden Markov Toolbox Version 3.3 01-Apr-99 and Coupled Hidden Markov Toolbox Version 1.1 01-Feb-01 Copyright (c) by Iead Re
DeNosingBaseOnXiaoBo
- 一种改进的基于PCNN神经网络和QPSO粒子行为的PSO的图像滤波算法，也可以较好地去除高斯噪声-Improved PCNN-based neural network and PSO behavior QPSO particle image filtering algorithm can also be better to remove Gaussian noise
levenberg
- This a java implementation of Levenberg-Marquardt algorithm to train properly a neural network. Levenberg-Marquardt, implemented from the general descr iption in Numerical Recipes (NR), then tweaked slightly to mostly match the results of their code.
fbm.2004.11.10
- 《Software for Flexible Bayesian Modeling and Markov Chain Sampling》是机器学习领域专家Neal编写的用于Bayesian和马尔可夫链Linux下的C语言工具包。很有名，也很权威。 -This software supports Bayesian regression and classification models based on neural networks and Gaussian processes, and Ba
Image-Restoration-with-BPNN
- 基于BP神经网络的高斯模糊图像复原的方法实现，结合了BP神经网络良好的非线性逼近功能，效果较传统的算法更好。-BP neural network based image restoration method of Gaussian blur implementation of BP neural network combines good nonlinear approximation function, the effect is better than traditional algorit
RBFyuanchengxu
- 在RBF神经网络学习过程中，I出F神经元先计算输入与中心之间的距离，然 后再对这一距离进行某种非线性变换。输出层和隐藏层分别完成不同的任务，这两层学习的策略也不相同。输出层是对线性权进行调整，采用的是线性优化策略， 因而学习速度较快。而隐藏层是对传递函数的参数进行调整，采用的是非线性优 化策略，因而学习速度较慢。 RBF算法选用高斯函数作为隐藏层传递函数时，由隐藏层来实现从 x哼R，(x)的非线性映射，由输出层来实现从R,(X)--->y。的线性映射。-In the R
The-adaptive-Neural-Network-
- 基本上实现这些类型的神经网络： 自适应线性网络（ADALINE） 多层多层感知器网络 广义径向基函数网络 动态细胞结构（DCS）网络与高斯或圆锥形的基础功能-There are blocks that implement basically these kinds of neural networks: Adaptive Linear Networks (ADALINE) Multilayer Layer Perceptron Networks Generalized
neural-network.rar
- matlab例程，主要实现神经网络的辨识（不是应用工具箱），其中包含多个子文件，包含高斯白噪声的生成，bp神经网络，hopfield神经网络等的辨识。,matlab routine identification of neural network (not application toolbox), which contains multiple subfolders containing white Gaussian noise generated bp neural network, hop
NETLAB-algorithms-for-PR
- NETLAB algorithms for PR+书籍代码。学习模式识别的很好的老外书籍。基础模型很多，代码很细致，有很多算法的实现细节，对于应用很有帮助，-chapter covers a group of related pattern recognition techniques and includes a range of examples to show how these techniques can be applied to solve practical problems.
classifier
- 简单的分类小程序。包括高斯混合模型、svm（调用函数）、logistic regression、和人工神经网络-Simple classification applet. Including the Gaussian mixture model, svm (calling function), logistic regression, and artificial neural networks
gaosijihanshushejifangzhen
- 把高斯基函数用matlab实现，方便以后对其的应用，可以应用到高斯径向基函数神经网络中,另外附加一份matlab中画图语句的指令说明-The Gaussian function using matlab facilitate its future application, can be applied to a Gaussian radial basis function neural network
RBFPID
- simulink高斯径向基函数神经网络的PID控制-simulink Gaussian radial basis function neural network PID control
RBF
- RBF神经网络：rbf原理：所谓径向基函数(Radial Basis Function 简称 RBF），就是某种沿径向对称的标量函数。通常定义为空间中任一点x到某一中心xc之间欧氏距离的单调函数，可记作 k(||x-xc||），其作用往往是局部的，即当x远离xc时函数取值很小。最常用的径向基函数是高斯核函数，形式为 k(||x-xc||)=exp{- ||x-xc||^2/（2*σ）^2） } 其中xc为核函数中心，σ为函数的宽度参数，控制了函数的径向作用范围。在RBF网络中，这两个参数往往是可