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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
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BP神经网络用于函数拟合与模式识别，用MATLAB编写的遗传算法路径规划，包括主成分分析、因子分析、贝叶斯分析。- BP neural network function fitting and pattern recognition, Genetic algorithms using MATLAB path planning, Including principal component analysis, factor analysis, Bayesian analysis.
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验证可用，关于神经网络控制，利用贝叶斯原理估计混合logit模型的参数。- Verification is available, On neural network control, Bayesian parameter estimation principle mixed logit model.
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手写体数字识别的程序，用了三种方法，贝叶斯，最近邻和BP神经网络，用MATLAB编写的，算法简单易懂，结构清晰-Handwritten digital recognition procedures, using three methods, Bayesian, Nearest Neighbor and BP neural network, written in MATLAB, the algorithm is easy to understand, clear structure
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Is a two hidden layer back propagation neural network, Bayesian parameter estimation principle mixed logit model, Foreign materials inside the source code.
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Bayesian parameter estimation principle mixed logit model, Chaos-based simulated annealing algorithm, On neural network control.
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本内容是有关机器学习的包含贝叶斯分类器，随机森林，支持向量机，神经网络，logistic多元回归等(The contents of this paper are machine learning, including Bayesian classifier, random forest, support vector machines, neural network, logistic multiple regression and so on)
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Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, Bayesian parameter estimation principle mixed logit model, On neural network control.
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Is a two hidden layer back propagation neural network, Including principal component analysis, factor analysis, Bayesian analysis, Achieve canonical correlation analysis.
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BP神经网络算法，贝叶斯-最小距离分类器，可以用于模式识别。(BP neural network algorithm, Bayesian minimum distance classifier, can be used for pattern recognition)
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概率神经网络(Probabilistic Neural Network)是由D.F.Speeht博士在1989年首先提出，是径向基网络的一个分支，属于前馈网络的一种。它具有如下优点：学习过程简单、训练速度快；分类更准确，容错性好等。从本质上说，它属于一种有监督的网络分类器，基于贝叶斯最小风险准则。(The rate neural network, first proposed in 1989, is a branch of the RBF network and is one of the fe
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第一次作业_基于分类算法的雷达状态识别
对于本数据集中的雷达状态识别，数据降维前使用朴素贝叶斯、支持向量机、神经网络的分类算法对于识别的准确率无太大影响；数据降维后使用神经网络算法最优，支持向量机算法其次，朴素贝叶斯算法较差。此外，训练样本越多，分类准确率有小幅度提高。(First Operation Radar State Recognition Based on Classification Algorithms For radar state recognition
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matlab实现一些基础的模式识别工作，如贝叶斯分类，聚类算法，bp神经网络(Matlab implements some basic pattern recognition work, such as Bayesian classification, clustering algorithm, BP neural network)
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