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Sector is a system infrastructure software that provides functionality for distributed data storage, access, and analysis/processing. It automatically manages large volumetric data across servers or clusters, even those over distributed wide area high speed networks. Sector provides simple tools and ...

This source can emulate function generator using sound card. This source is very useful for sound card operation and waveform research.

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 ...

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 ...

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 techniques while still contain ...

Forest quanity remote sensing reesearch, it is a useful and important paper and helpful to our research.

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 ...

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: ...

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 ...

％％％ Demos for PUMA algorithms ％％％ We present four matlab demos for PUMA. demo1, demo2, demo3, and demo4 illustrate PUMA working with different parameters and with four different images. All you need to do is to run each of the demos. Please be sure that all the files are put on an accessibl ...