Greypre

说明：  MATLAB小波分析的学习资料 ppt 有需要的朋友可以看看(MATLAB Wavelet Analysis of the learning materials ppt can see a friend in need)

惯导解算代码，使用四元数理论，解算过程，我是来骗分的，行了不？20字了不？懒得改你脚本而已(The INS solver code, using the quaternion theory, solving process, I deceive points, the line does not? 20 words do not? Too lazy to change your script.)

基于RD算法的机载SAR点目标matlab仿真程序(The matlab code is about the point target simulation of airborne SAR based on RD algorithm )

ADC report Matlab implementation

说明：  一个自己做的MATLAB图象处理程序，已经上传了依次，没有成功，重新上传。重点是对BMP图象的各种操作以及MATLAB的GUI编程！(a MATLAB own image processing procedures, have uploaded followed, without success, to re-upload. Focus BMP images of the various operational and MATLAB GUI Programming!)

说明：  倒立摆系统PID控制研究，里边有PID与模糊PID控制角度的对比。(PID Control of Inverted Pendulum, inside a PID control and fuzzy PID angle contrast.)

线性预测在MATLAB中的实现，非常具有参考价值的文档(Linear prediction in the MATLAB implementation of the document is a reference value)

说明：  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.)

這一篇論文的標題為「比較編碼和未編碼縱向和橫向層狀結構的MIMO-OFDM系統」是2007發表的(This is a paper entitled )

对QAM的频谱、散图、眼图以及误码率进行了仿真。使用matlab语言。(QAM spectrum of scattered diagram, eye diagram and BER simulation. Using matlab language.)