matlab_zhiling(word)

FrameWork logic user guide for Innovative integration X5 EVM

matlab教程matlab试题与解析MATLAB试题解答和方法分析(matlab)

基于最小二乘法RBF神经网络MATLAB程序 用于神经网络学习(rbf nn based on ls)

Simulation for DC Motor selection. It includes two files, which are DCMotor_Trj.m and DCMotor.mdl. First of all, you run the DCMotor_Trj.m for generating the reference trajectory. Then, you open the Simulink file(DCMotor.mdl) and run! You may change DC Motor parameters.

本文应用SMQT和 SPLIT UP SNOW 分类器来完成对人脸的检测。(The purpose of this paper is threefold: firstly, the local Successive Mean Quantization Transform features are proposed for illumination and sensor insensitive operation in object recognition. Secondly, a split up Sparse Network of Winnows is presented to speed up the original classifier. Finally, the features and classifier are combined for the task of frontal face detection. Detection results are presented for the MIT+CMU and the BioID databases. With regard to this face detector, the Receiver Operation Characteristics curve for the BioID database yields the best published result. The result for the CMU+MIT database is comparable to state-of-the-art face detectors.)

Dynamic trianglur network (DTN) implementation in matlab source code

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)

Easy guide for learning Minitab

首先对图像进行了边缘检测，设计相应的结构元素对图像进行腐蚀，再进行图像聚类和填充图像。(First, the image edge detection, the design of structural elements corresponding to the image etched image clustering and then fill the image.)

基于云模型雾化算法的实现。该程序实现了雾化算法在全局范围内的最优搜索（二维，十维，三十维）。(Aerosol cloud model based algorithm. The process of atomization Algorithm for the Global Optimum Search in the context of (two-dimensional, 10 dimensional, 30 dimensional).)