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实现了在地震记录中拾取地层的Q值，然后对Q值进行补偿(Pickup achieved in the formation of the Q value of the seismic records, and Q values ​ ​ to compensate for)

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.)

提供了Matlab平台下高阶统计量的常用算法以及运算函数。并且给出了时间延迟估计等实际应用的算例(Matlab platform provides a higher-order statistics of the commonly used algorithms and computing functions. And gives the time delay estimation in practical applications, such as the numerical example)

bit error rate of quadrature modulation.

自己按J David的方法做的7个Hu时刻，用于边缘检测(7 HU moments，similitude Moments，matlab)

通过光速不变原理介绍相对论时间膨胀公式和长度收缩效应公式，并举例进行了说明。用曲线显示时间膨胀与物体速度的关系，显示长度收缩与物体速度的关系。(Through the principle of constancy of light, relativistic time dilation formula and length contraction effect formula, and examples are described. Curve shows the time dilation and the speed of the object, showing the length contraction and the speed of the object.)

采用时频聚集性较好的线性调频信号作为线性时不变系统输入激励，采用Gabor字典作为过完备原子库。在利用传统系统辨识法之前先利用稀疏分解算法将输出信号进行去噪处理，显著提高系统辨识精度。 具体包括互谱算法，信号的Gabor稀疏分解的详细代码(Space can be a time for sparse decomposition to solve the problem of huge memory needed。This approach, combined with the rapid decomposition of FFT for signal ,so as to achieve satisfactory results.)

集中式和联邦式卡尔曼滤波在组合导航中的数据融合和数据滤波的应用(The federated filtering theory was proposed by Carlson based on disperse filtering)

BAN Network in human body

Matlab矩阵数据与外部程序交换,目的是使用 Ctrl+V 拷贝空间中的matlab变量数据到Origin,或其他软件.(Copy the Matlab matrix data on clipboard and feed data into excel or notepad using Ctrl+V .)