power_xfosaturable

关于在MATLAB上的仿真平台 仿真技术的使用教学PPT(In MATLAB simulation platform on the use of simulation technology teaching PPT)

Finite Volume Method 流体仿真代码 利用TDMA算法计算二维矩阵 从而计算出二位场内各点的性质 可以通过修改步长和网格大小实现算法研究(A computational fluid dynamics code for determine the property of a two-dimensional plate by using Finite Volume Method. Grid size and time step are free to change in this code.)

介绍了支持向量机(SVM)中广泛采用的算法-分解算法 ,总结了其收敛性证明的 总体思路并对目前最流行的 SVM算法库LIBSVM进行了详细的分析与研究(Describes support vector machine (SVM) algorithm is widely used- decomposition algorithm, summed up the general idea of ​ ​ the convergence proof and the most popular SVM library LIBSVM algorithm carried out a detailed analysis and research)

This code calculates frame difference to detect moving object in video

watermark the data in image using svd algorithm...coding only for embedding watermark

采用 Welch法在matlab中进行功率谱密度计算(Welch method using power spectral density calculation in matlab)

应用鸟群算法（PSO）优化全局神经网络权值，可以使用(Applications birds (PSO) algorithm to optimize the overall neural network weights, you can use)

对振动信号进行分析，通过WVD进行视频分析(Vibration signals were analyzed and video analyzed by WVD)

说明：  本电子书包涵了各种算法的MATLAB实现，具体包括插值方法、数值分析、常微分方程的差分法、方程求根、线性方程组的迭代法、线性方程组的直接法等等，还包括习题参考答案和MATLAB文件汇集~~(The e-book encompasses the MATLAB implementation of various algorithms, specifically including interpolation methods, numerical analysis, ordinary differential equations using finite difference method, equation Root, linear equations iterative method, the direct method of linear equations, etc. The answer also includes exercises and MATLAB files reference collection ~ ~)

deep learning一般是学习的层次结构，它也是有一定理论依据的，即模拟人脑的大脑皮层工作，因为大脑皮层的视觉区域也是分层次工作的，越底层的视觉皮层对那些底层特征就越敏感。综上所述，feature learning有这么多应用需求的驱动和生物神经理论上的支持，注定它能够在AI领域中发挥一定的作用。一些实验表明，有些feature learning学习到的特征几乎比所有其它的特征效果要好，比如本文中的ISA模型就是其中一个。(deep learning hierarchy of learning, it is also a certain theoretical basis that simulate the human brain' s cerebral cortex, visual areas of the cerebral cortex is hierarchical work, the more the bottom of the visual cortex is more sensitive to those underlying characteristics . In summary, feature learning so many application needs the support of the drive and biological neural theoretically doomed it to be able to play a certain role in the field of AI. Some experiments show that some feature learning learning to feature almost better than all the other features of the effect of the ISA model such as this is one.)