8~13

matlab仿真，适合3/4、2/3、5/6、1/2，速率的打孔程序(matlab simulation, for 3/4, 2/3, 5/6, 1/2, the rate of drilling procedure)

程序实现设计一单一感知器神经元以及采用神经网络拟合奇异函数。压缩包中还包含相关的参考资料。(Design a program to achieve a single sensor neurons and neural networks fitting singular function. Compressed package also contains the associated reference materials.)

数字预失真Wiener模型的matlab实现(Digital predistortion Wiener model matlab implementation)

超宽带定位系统，较好的一本书，涉及很多方面的内容(Ultra-wideband positioning system, a good book, involving many aspects)

These files contain all the code necessary to run the example in the Webinar "Signal Processing for Machine Learning in MATLAB". They also include code to automate the download and preparation of the dataset used. In that webinar we presented an example of a classification system able to identify the physical activity that a human subject is engaged in, solely based on the accelerometer signals generated by his or her smartphone. We used consolidated signal processing methods to extract a fairly small number of highly-descriptive features, and finally trained a small Neural Network to map the feature vectors into the 6 different activity classes of a pre-recorded dataset. The topics discussed include: * Signal manipulation and visualisation * Design and application of digital filters * Frequency-domain analysis * Automatic peak detection * Feature extraction from signals * Train and test of simple Neural Networks

GIF动画式图片集的制作，很实用，可将一些照片连起来。(Animated GIF image sets were very practical, you can put together some pictures)

迭代法 OTSU法和局部阈值分割的matlab实现，测试可用(OTSU method, iterative method and local thresholding segmentation matlab implementation, testing available)

Simulink block diagram of simple Antilock Braking System control project report

模糊自适应PID控制的报告，后面带简单的程序，可以运行，就是抄的部分刘金琨的程序。不懂图的含义可以参考刘金琨的先进PID控制MATLAB仿真。(It s a simple report and simple simulink program about the Fuzzy-PID.)

Backpropagation, an abbreviation for backward propagation of errors , is a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of a loss function with respects to all the weights in the network.