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pcf8563t驱动程序
- PCF8563 的驱动程序，用两个普通的IO口模拟I2C总线，包括100KHZ（T=10US）的标准模式选择和400KHZ的快速模式选择，默认11.0592MHZ的晶振-PCF8563 of the driver, with two ordinary analog IO I2C bus, including the extremely low distortion (T = 10US), the standard model selection and 400KHZ fast mode sele
libsvm-2.81
- Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It can solve C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic
svm_v0.01beta.tar
- New in this version: Support for multi-class pattern recognition using maxwins, pairwise [4] and DAG-SVM [5] algorithms. A model selection criterion (the xi-alpha bound [6,7] on the leave-one-out cross-validation error). -New in this version
ReversibleJumpMCMCSimulatedAnneaing
- This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global se
BPC++
- Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic mo
particle-filter-mcmc
- 该程序为基于粒子滤波的一种新算法,综合MCMC Bayesian Model Selection即MONTE CARLO马尔克夫链的算法,用来实现目标跟踪,多目标跟踪,及视频目标跟踪及定位等,解决非线性问题的能力比卡尔曼滤波,EKF,UKF好多了,是我珍藏的好东西,现拿出来与大家共享,舍不得孩子套不着狼,希望大家相互支持,共同促进.-the program based on particle filter for a new algorithm, Integrated Bayesian MCMC
11
- 本文介绍了医学信号分析的常用方法，着重介绍了神经网络模式识别，包括他的优点及不足，最后介绍了神经网络的模型选择。-medical signal analysis methods commonly used to highlight the neural network pattern recognition, including his strengths and weaknesses, and the final presentation to the neural network model
gengamma
- Bayesian Model Selection
rjGaussian
- gaussian algorithm for Bayesian Model Selection
smcdemo1
- smcdemo1 for Bayesian Model Selection
rjMCMCsa
- On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and
On-Line_MCMC_Bayesian_Model_Selection
- This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation a
svm
- libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic mo
svm_v0.55beta
- 最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, \"The Nature of Statistical Learning Theory\", Springer-Verl
autolife
- Autolife模型是一个能够进行“开放式进化”的人工生命系统。每个Agent模型采用可以变化规则表长度的有限自动机模型建模。一方面Agent可以进行自我繁殖，同时模型中的选择机制没有采用显式的适应度函数而是采用能量消耗的简单模型而自发涌现出来，所以可以认为Agent模型是一个类Tierra系统。然而与Tierra、Avida等数字生命模型不同的是，Autolife模型进行了大大的简化，它界面友好，操作直接。虽然没有给每个Agent装配一个虚拟计算机，但是Agent与环境的耦合则可以看成一个图灵
bvsgs
- Bayes model averaging with selection of regressors - This program can be utilized for Bayesian Variable Selection using Gibbs Sampler-Bayes model averaging with selection of regressors- This program can be utilized for Bayesian Variable Selection usi
pr2007.pdf
- The BYY annealing learning algorithm for Gaussian mixture with automated model selection
pso_svm
- svm model selection by pso
BayesFactor
- bayes factor for model selection
BMS (1)
- bayesian model selection among dfferent models