planning-problem

图像处理函数 各类函数的具体使用方法介绍(Matlab)

说明：  OFDM的接收和发射，是用Matlab编程实现的，希望供大家参考学习！(OFDM receiver and launch, using Matlab programming, I hope for your reference learning!)

基于Matlab系统的信号FFT频谱分析与显示(Matlab FFT-based spectral analysis system signal and display)

说明：  人脸识别matlab程序 with a principal components analysis for a set of face images as the theme(Face recognition matlab procedures with a principal components analysis for a set of face images as the theme)

The following Matlab project contains the source code and Matlab examples used for speed control of a dc motor. The goal of this assignment was to develop a Speed control system for a DC motor.

120 DEGREE MODE OF 3 PHASE INVERTER

考虑L的三个不同值：L＝256（3个数据段），L＝128(7个数据段)和L=64（15个数据段）。各自的谱估计图如上图所示。可以明显的看到，加窗明显的减小了频谱上的假谱峰，但也更加进一步平滑了谱峰。所以，对于L＝64的情况，在ω＝0.8π的谱线可以很确定的辨认，但是那两个靠近的谱峰不容易区分。对于L＝128的情况，这种情况提供了在分离和检测间最好的均衡。当然，对于在L＝256时的情况，效果是更好的，能够从谱估计图上明显的分辨出三条谱线的存在以及它们幅度关系的强弱。 除了Welch法外，还可以采用对多个周期图求平均的功率谱估计方法的其他方法如Bartlett法等等，在功率谱估计上也能取得较好的结果。(consider three different values : L = 256 (3 data), L = 128 (7 data) and L = 64 (15 data). Their spectral estimation map as shown in Fig. It is clear to see that increase significantly decreasing window of the spectrum of false peaks, but much more to further smooth the peaks. Therefore, L = 64, in the case = 0.8 spectrum can determine the identification, but that the two peaks around is not easy to distinguish. L = 128 for the situation, which provided the separation and detection among the best balanced. Of course, L = 256 in the case, the effect is better, from the spectral estimation map clearly distinguish between the three lines of the existence and their relationship to the rate of strength. In addition to Welch law, but also can be used to map multiple cycle for the average power)

波束形成，直方图方位估计的算法演示程序，还有加权直方图方位统计(Beamforming，The observed signal is variable Fractional conversion)

Matlab教程第六章案例，时间序列分析与计量(Matlab Guide Chapter cases, time series analysis and measurement)

matlab图像分割实例，检测运动汽车，割调用库函数实现，带注释，简单易懂；(matlab image segmentation example, detection of vehicle movement, cutting call the library functions, with comments, easy to understand )