mean-shift

dct2的编程实现，用来压缩灰度图像，需要修改输入的图像名，保持和程序里的名称一致(dct2' s programming is used to compress grayscale images, need to modify the input image name, the name of maintaining and procedures where the same)

求解陀螺仪的姿态角，采用四元素的四阶龙格库塔法求解，含姿态初始四元素的确定。(Solving gyro attitude angle, using the four elements of the fourth-order Runge-Kutta method to solve, including the initial four elements determined attitude.)

说明：  matlab简单例程，可以熟悉矩阵的建立、提取、逻辑循环等功能(matlab simple routine, familiar with the matrix can be set up, extraction, logic cycle and other functions)

在加噪声的情况下，利用pso（粒子群算法）辨识NARMAX模型(实例一）(In the case of additive noise, the use of pso (PSO) identify NARMAX model (Example I))

仿真对象如下： 其中， v( k )为服从N (0,1) 分布的白噪声。输入信号u ( k) 采用M 序列，幅度为 1。M 序列由 9 级移位寄存器产生，x(i)=x(i-4)⊕x(i-9)。 选择如下辨识模型： 加权阵取Λ = I。 衰减因子β = 0.98，数据长度 L = 402。 辨识结果与理论值比较，基本相同。辨识结果可信 (he simulation object is as follows: among them, v (k) to obey N (0, 1) distribution of white noise. The input signal u (k) using M sequence, amplitude is 1. M sequence by 9 level shift register generation, x (I) = x (I- 4) ⊕ x (I- 9). Choose the identification model: weighted array take Λ = I. Attenuation factor β = 0.98, the data length L = 402. Identify the theoretical calculation and comparison, basically the same. Identification results are reliable)

FIR数字滤波器在工程上运用广泛．窗函数法设计FIR数字滤波器是典型的设计方法。目前。相关课程的教科书对窗函数法设计FIR 散字滤波器这部分内容讲解不够细致，学生掌握感到有难度。本文针对窗函数法设计FIR数字滤波器的相关问题．即数字滤波器与模拟样本 滤波器的关系、截断点如何取值和数字滤波器的线性相移特性，结合实例进行分析。并借助Matlab仿真软件对设计进行了分析和验证．(FIR digital filters widely used in engineering. Window method is a typical design FIR digital filter design methods. Present. Related courses textbooks window functions designed FIR filter scattered words to explain this part carefully enough, students are difficult to master. This window function method for the design of FIR digital filters related issues. Samples of the digital filter and analog filter between values and the cut-off points to the linear phase shift digital filter characteristics, with examples for analysis. And using Matlab simulation software design analysis and verification.)

用matlab语言对雷达系统进行了仿真，相干积累，回波(Matlab language with a simulation of the radar system, coherent accumulation, echo)

signal modulation it is good for you

数据整理，数据和标签和样本数量之间的匹配，当然也可以用其他方法，仅供参考(Data collation, matching between data and label and sample quantity, of course, other methods can be used, for reference only)

说明：  本程序利用改进的CHOW算法，仿真了自适应OFDM系统的性能，并画出了SNR-BER仿真图。对于学习OFDM自适应资源分配者有很帮助。(This procedure improved CHOW algorithms, simulation of the adaptive OFDM system performance, and draw the SNR-BER simulation Fig. Adaptive OFDM for learning the distribution of resources to help those who have.)