chaoliushuoming

Partial Least Squares regression bilinear factor model 的输出源码(Partial Least Squares regression bilinea r factor model output FOSS)

使用matlab程序编写的雷达目标航迹跟踪小例程，主函数是进行雷达数据处理，通过CEvHBv分析，主成分提取，rjxPEom降噪等处理后得到的运动轨迹曲线。 (Matlab programming using radar target tracking small track routines, the main function is radar data processing, through CEvHBv analysis, principal component extraction trajectory after rjxPEom noise reduction processing curves obtained. )

关于数学实验的几个matlab程序，里面有一个说明的幻灯片(Mathematical Experiments on several matlab program, which has a description of the slide)

MIT_Maximizing AUV Slow Speed Performance (by Phillip J.LeBas)

The goal of the HumanEva dataset is to develop new techniques, technology, and algorithms for the automatic articulated pose estimation and tracking of humans. Brown University is involved in an ongoing effort to develop this dataset of synchronized video and motion capture data.

处理信号的时频分析，D-S证据理论数据融合，AHP层次分析法计算判断矩阵的最大特征值。( When processing a signal frequency analysis, D-S evidence theory data fusion, Calculate the maximum eigenvalue judgment matrix of AHP.)

深度神经网络在函数近似中表现优越，然而需要从头开始训练。另一方面，贝叶斯方法，像高斯过程（GPs），可以利用利用先验知识在测试阶段进行快速推理。然而，高斯过程的计算量很大，也很难设计出合适的先验。本篇论文中我们提出了一种神经模型，条件神经过程（CNPs），可以结合这两者的优点。CNPs受灵活的随机过程的启发，比如GPs，但是结构是神经网络，并且通过梯度下降训练。CNPs通过很少的数据训练后就可以进行准确的预测，然后扩展到复杂函数和大数据集。我们证明了这个方法在一些典型的机器学习任务上面的的表现和功能，比如回归，分类和图像补全(Deep neural networks perform well in function approximation, but they need to be trained from scratch. On the other hand, Bayesian methods, such as Gauss Process (GPs), can make use of prior knowledge to conduct rapid reasoning in the testing stage. However, the calculation of Gauss process is very heavy, and it is difficult to design a suitable priori. In this paper, we propose a neural model, conditional neural processes (CNPs), which can combine the advantages of both. CNPs are inspired by flexible stochastic processes, such as GPs, but are structured as neural networks and trained by gradient descent. CNPs can predict accurately with very little data training, and then extend to complex functions and large data sets. We demonstrate the performance and functions of this method on some typical machine learning tasks, such as regression, classification and image completion.)

收集的一组跟噪声产生以及消除、衡量消噪性能指标的MATLAB仿真源代码，每个文件夹下都附有对该代码的注解！(gathered with a group and the elimination of noise, the weighing-noise performance indicators MATLAB simulation source code, Each folder with all of this code notes!)

用MATLAB合成歌唱祖国，包括初步与简单改变（包络）(Ode to the Motherland synthesis using MATLAB, including the initial and simple to change (the envelope))

AN MATLAB DESIGN OF PV ARRAY