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其他 Samples are organized by chapter, and then by "application" or example name. You should open a proje
Samples are organized by chapter, and then by "application" or example name. You should open a project in Visual Studio .NET through the .sln (solution) file.
Note that Visual Studio .NET automatically creates various temporary and debugging files in the obj and bin sub-directory for each project. ...
matlab例程 LiScNLS is a Matlab application for the numerical study of some nonlinear differential equations o
LiScNLS is a Matlab application for the numerical study of some nonlinear
differential equations of the form Lu=Nu, using the Lyapunov-Schmidt method.
Downloading the LiScNLS package creates a new LiScNLS folder on the computer.
SQL Server LiteSQL is a C++ library that integrates C++ objects tightly to relational database and thus provide
LiteSQL is a C++ library that integrates C++ objects tightly to relational database and thus provides an object persistence layer. LiteSQL supports SQLite3, PostgreSQL and MySQL as backends. LiteSQL creates tables, indexes and sequences to database and upgrades schema when needed.
数学计算 计算高斯各阶导函数的C程序 Computing Gaussian derivative waveforms of any order. Dgwaveform efficiently cre
计算高斯各阶导函数的C程序
Computing Gaussian derivative waveforms of any order.
Dgwaveform efficiently creates Gaussian derivative wavelets
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 ...
数学计算 The software implements particle filtering and Rao Blackwellised particle filtering for conditionall
The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generi ...
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 ...