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DSP编程 The line echo canceller (LEC) is designed to provide the maximum attainable transparent voice qualit
The line echo canceller (LEC) is designed to provide the maximum attainable transparent voice quality for
de-echoing of a PSTN or POTS connection in voice-over-LAN systems with internal delays, or on a codec end of a telecom switch,基于TI 54X/55X平台
数学计算 求特征值与特征向量的程序
求特征值与特征向量的程序，通过methode de LU思想设计。
人工智能/神经网络 This manual describes how to run the Matlab® Artificial Immune Systems tutorial presentation deve
This manual describes how to run the Matlab&reg Artificial Immune Systems tutorial presentation developed by Leandro de Castro and Fernando Von Zuben. The program files can be downloaded from the following FTP address: ftp://ftp.dca.fee.unicamp.br/pub/docs/vonzuben/lnunes/demo.zip
The tour is self- ...
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 ...
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, 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 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: ...
数学计算 This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps t
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 and details are presented in: Christophe Andrieu, N ...
数学计算 This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hier
This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that n ...
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 ...