ToolBox

结构动力分析计算节点垂直方向的动力响应matlab程序(Dynamic Analysis of compute nodes vertical dynamic response matlab program)

水果图像的分类处理，与以往不同的是改程序可以直接对图片进项处理(Fruit image classification, and different from the past to change the program proceeds directly to the picture processing)

Changed in hostfs_args before the kernel starts running.

说明：  跳频通信中模式相加的原代码（配合Mmod.m，reMmod.m,U.m）一起使用。（附MATLAB库函数说明）(The sum of frequency-hopping mode of communication in the original code (with Mmod.m, reMmod.m, Um) use. (With MATLAB library function description))

各种波形的matlab生成 可以观察波形图(Matlab various waveforms generated waveform can be observed)

高阶谱分析,用于检测两个信号的延时情况,应用方面非常广泛，适用于阵列信号处理、雷达信号处理等.包含了TDEL文件和tdeb.m(Higher-order spectral analysis for the detection of two signals delay the case, the application is very widely used for array signal processing, radar signal processing. Contains TDEL files and tdeb.m)

粒子滤波算法在非线性系统中得到了广泛的应用，其精度取决于目标概率函数和重要性函数是否相近，并且样本退化问题也影响了算法的性能。针对粒子滤波算法中样本退化的问题，本文提出一种基于奇异值分解的粒子滤波算法。该算法通过使用奇异值分解方法得到的重要性概率密度函数更接近于目标概率分布，降低样本退化的影响，提高了滤波器的精度，然后在列车组合定位系统的数学模型中应用该算法进行仿真实验。 (Particle filter algorithm for nonlinear systems is widely used, its accuracy depends on whether the target probability function and importance of the functions are similar, and sample degradation also affects the performance of the algorithm. For particle filter algorithm sample degradation problem, this paper proposes a particle filter algorithm based on singular value decomposition. The algorithm by using singular value decomposition of the importance of the probability density function method to get closer to the target probability distribution, reduce sample degradation, improve the accuracy of the filter, and then apply the algorithm in combination mathematical model train positioning system simulation experiments. The simulation )

退火粒子群优化算法（SAPSO），matlab代码，仅供学习(Annealing particle swarm optimization (SAPSO), matlab code, only to learn)

说明：  古典四级四阶显式Runge—Kuuta方法和隐式二级四阶Runge-Kutta的范例(Classical four-order explicit Runge-Kuuta method and implicit second-order fourth-order Runge-Kutta example)

说明：  图像的双线性插值放大算法中，目标图像中新创造的象素值，是由源图像位 置在它附近的2*2 区域4 个邻近象素的值通过加权平均计算得出的。 双线性内插 值算法放大后的图像质量较高，不会出现像素值不连续的的情况。然而次算法具 有低通滤波器的性质，使高频分量受损，所以可能会使图像轮廓在一定程度上变 得模糊。 (Bilinear interpolation algorithm to enlarge the image, the target image in the newly created pixel value is determined by the source image position in its area near the 4 2* 2 the value of neighboring pixels calculated by the weighted average. Bilinear interpolation algorithm to enlarge the image quality after the high pixel value does not appear the situation is not continuous. However, sub-algorithm has low-pass filter nature of the damage to the high frequency components, it may make the image contour to some extent become blurred.)