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ini catatn jul yg sulit dan susah untuk penelitian

文章中建立了被动式导引头的模型，并对其仿真分析(Established a model of passive seeker, and the simulation analysis)

利用Gabor滤波器进行特征提取，在信号与图像处理领域有着广泛的应用。参考文献“Efficient Computation of Gabor Features”(Gabor fi lter responses are widely and successfully used as general purpose features in many computer vision tasks, such as in texture segmentation, face detection and recognition, and iris recognition.)

说明：  非负矩阵分解nmf，通过迭代w和h，收敛后输出最终w和h。(Non-negative matrix decomposition nmf, through iteration W and h, the final W and H are output after convergence.)

How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments. (How the K-mean Cluster workStep 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (Nk) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3. Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4. Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.)

matlab matlab source code lic lice

一个曲柄滑块机构的matlab仿真代码，包括其运动仿真，以及变量变化曲线图的生成。(A slider-crank mechanism of matlab simulation code, including its motion simulation, and variable changes in graph generation.)

时频分析工具，经典工具箱，包括短时傅里叶变换等实用函数 (Time-frequency analysis tools, classic toolbox, including the short time Fourier transform and other utility functions)

newton generalized numerical method

用于产生gamma分布的噪声序列，以及分析gaussian噪声的各参数。(Gamma distribution used to generate the noise sequence, as well as the analysis of Gaussian noise in each parameter.)