pmsm

一个matlab的图像边缘源码，打开后带参运行，图像处理(bianyuanlianjieyuanma)

现成的——leach协议剩余节点和时间关系的awk脚本(Ready-made- leach agreement between the remaining nodes and the time awk script)

用MATLAB产生M序列作为系统的输入，根据传递函数，仿真输出，并得出输入的自相关函数和输入输出的互相关函数。(M sequence generated by MATLAB as input, in accordance with transfer function, simulation output, and come to enter the auto-correlation function and the input and output of the cross-correlation function.)

OFDM同步Ls算法的MATLAB仿真程序，希望对你有帮助(OFDM synchronization Ls algorithm MATLAB simulation program, want to help you)

Matrix inverse by Gauss-Jordan elimination

带动量项的BP算法程序求解XOR问题，权值更新为批处理方式。(driven volume items BP algorithm XOR problem solving process, the right to update the value of the batch mode.)

短时傅里叶变换，窗函数是冲击函数时的STFT，窗函数是常数数时的STFT(Short-time Fourier transform, the window function is the function of the impact of STFT, the window function is constant when the number of STFT)

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.)

doubly fed induction motor simulation using simulink

Matlab程序为清华大学胡广书版信号处理的上机习题答案(Matlab procedures for Qinghua University HU-book version of the signal processing on the answer machine Exercises)