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matlab例程 MATLAB5语言手册.rar pdf格式
MATLAB5语言手册.rar pdf格式
matlab例程 MATLAB手册,提供使用matlab5的实践性指导
MATLAB手册,提供使用matlab5的实践性指导，简述对矩阵、数据、图像等处理操作
人工智能/神经网络 遗传算法工具箱支持平台matlab5以上版本
遗传算法工具箱支持平台matlab5以上版本
matlab例程 Matlab5参考书 1.介绍主要的模块和大体的功能 2.一些函数的详细信息
Matlab5参考书
1.介绍主要的模块和大体的功能
2.一些函数的详细信息
数学计算 专家PID控制MATLAB程序
专家PID控制MATLAB程序，在MATLAB5。3以上版本运行
人工智能/神经网络 n this demo, we show how to use Rao-Blackwellised particle filtering to exploit the conditional inde
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 Bayesian Networks. This detailed discussion of the ...
matlab例程 In this demo, we show how to use Rao-Blackwellised particle filtering to exploit the conditional ind
In 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 Bayesian Networks. This detailed discussion of th ...
matlab例程 The algorithms are coded in a way that makes it trivial to apply them to other problems. Several gen
The algorithms are coded in a way that makes it trivial to apply them to other problems. Several generic routines for resampling are provided. The derivation and details are presented in: Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas and Eric Wan. The Unscented Particle Filter. Technical re ...
人工智能/神经网络 On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carl
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 model parameters as unknowns. The derivation and deta ...
matlab例程 In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve r
In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: ...