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On-Line_MCMC_Bayesian_Model_Selection
- 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 a
Reversible_Jump_MCMC_Bayesian_Model_Selection
- 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 paramete
15883869kalmanfilter
- 卡尔曼滤波对目标跟踪进行滤波是不错的，在程序中可以看出，也可以自己修改该算法，一适合自己的开发，然后进行监控-Kalman filter for target tracking filter is good, can be seen in the proceedings, but also can modify the algorithm, one for their own development, and then monitor
FFTjs
- 快速傅里叶算法FFT，避雷器监测器信号处理中的算法解析。-Fast Fourier algorithms FFT, surge arrester monitor resolution signal processing algorithms.
chenlieguan
- 世界名画陈列馆由nm × 个排列成矩形阵列的陈列室组成。为了防止名画被盗， 需要在陈列室中设置警卫机器人哨位。每个警卫机器人除了监视它所在的陈列室外，还可以监视与它所在的陈列室相邻的上、下、左、右4 个陈列室。试设计一个安排警卫机器人哨位的算法，使得名画陈列馆中每一个陈列室都在警卫机器人的监视之下，且所用的警卫机器人数最少。 算法设计： 设计一个优先队列式分支限界法，计算警卫机器人的最佳哨位安排，使得名画陈列馆中每一个陈列室都在警卫机器人的监视之下，且所用的警卫机器人数最
Multiscale-NPE-FOR-fault-detection
- 首先对一段正常工况下的历史数据进行离散小波分解,对不同尺度下的小波系数建立相应的NPE模型.经过多层小波分解,建立相应的统计量对过程进行监控-First discrete wavelet decomposition of some normal conditions of historical data, the NPE model wavelet coefficients in different scales. Multilayer wavelet decomposition, the es
4-Channels-Temperatures-Monitor
- Source code for 4 channels monitor.
sgu262
- sgu262：Symbol Recognition(状压DP) 题目大意： 给出k个n∗ m的01矩阵Si，求出一个1尽量少的n∗ m的01矩阵P，满足k个矩阵与该矩阵的交互不相同，也就是说通过该矩阵能表示出给出的k个矩阵。-262. Symbol Recognition time limit per test: 0.25 sec. memory limit per test: 65536 KB input: standard output:
FFT256
- FFT蝶型算法程序，用于完成FFT的可快速变换，相对于其他程序，本例子可以监控每个数据的变换结果，方便用户进行理解。-FFT butterfly algorithm program for the completion of the FFT can be quickly converted with respect to other programs, the present example can monitor the results of each data conversion, use
mrdpca
- mrdpca-故障诊断 引入动态过程，改进主成分分析，能更好的监测故障-mrdpca-fault diagnosis Dynamic process is introduced to improve the principal component analysis, which can better monitor the fault.
S参数提取
- FDTD中利用监视器电场提取S11，S21，S12，S22参数(In FDTD, S11, S21, S12, S22 parameters are extracted from the monitor electric field.)