资源列表
netlist_CH3
- As a consequence, more exact models of devices can be retained for analysis rather than the approximate models commonly introduced for the sake of computational simplicity. A computer icon appears in the margin with each introduction of MATLAB
netlist_CH2
- As a consequence, more exact models of devices can be retained for analysis rather than the approximate models commonly introduced for the sake of computational simplicity. A computer icon appears in the margin with each introduction of MATLAB
netlist_CH1
- As a consequence, more exact models of devices can be retained for analysis rather than the approximate models commonly introduced for the sake of computational simplicity. A computer icon appears in the margin with each introduction of MATLAB
LearningPatternClassificationASurvey
- 模式识别学习综述.该论文的英文参考文献为303篇.很有可读价值.Abstract— Classical and recent results in statistical pattern recognition and learning theory are reviewed in a two-class pattern classification setting. This basic model best illustrates intuition and analysis t
hmok5
- java语言实现的神经网络,包括源程序,这是简单的实现方式,给初学着一个参考!
work
- MATLAB教程中提到的根据C-14计算化石生活年代的程序,放在MATLAB文件夹下的工作目录中,使用C14命令即可运行,根据教程要求写成然后换成中文提示方式,呵呵,方便处学者!
hmok4
- 基于Visual C++开发的BP神经网络源程序 基于Visual C++开发的BP神经网络源程序
hmok3
- MATLLABE编程,STPHEN J.CHAPMAN著,MATLLABE中文站首发,
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
hmok2
- 应用概率神经网络预测股市的方向变化 应用概率神经网络预测股市的方向变化
hmok
- 概率神经网络翻译资料,较为详细的解说了PNN网络的特点和网络结构以及几种优化结构
EMdemo
- n this demo, we show how to use Rao-Blackwellised particle filtering to exploit the conditional independence structure of a simple DBN. The derivation and details are presented in A Simple Tutorial on Rao-Blackwellised Particle Filtering for Dynamic