ANT_TSP

说明：  详细讲述matlab的使用方法和基本命令，包括如何建立M文件等等(Matlab detail the use and basic commands, including how to create the file, and so M)

说明：  PQ法潮流计算，matlab实现，给定配网模型参数就可得到各个节点参数(PQ method flow calculation, matlab achieve, given the model parameters of the distribution network can get each node parameters)

Generate maximal length and gold sequence and proves its autocorrelation and cross correlation properties.

该程序源代码实现了OFDM通信系统性能的仿真，调制方式有BPSK,QPSK,MSK,QAM,信道为AWGN和Rayleigh信道，并对有插入导频的符合IEEE802.11a的OFDM系统进行了仿真。(The program source code to achieve the performance of OFDM communication system simulation, modulation has BPSK, QPSK, MSK, QAM, for the AWGN channel and Rayleigh channel, and have inserted the line with the IEEE802.11a pilot of OFDM system simulation.)

电子科技大学《信号检测与估计课件，研究加性噪声中的检测与估计(Signal detection and estimate )

MATLAB高级讲义实例4(控制系统的分析方法)(MATLAB examples of senior notes 4 (Control System Analysis Method))

用于交通流模拟使用的源代码，复制到matlab上即可使用。(Source code for traffic flow simulation used, copied to the matlab can be used.)

实现信号的小波分解和重构，其中小波分解是三层小波分解(Realization of wavelet decomposition and reconstruction of signals)

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)

这是一个基于线性矩阵的神经网络控制程序，它比普通的更简单，因为其应用的参数较少。(This is a learning model for matrix-based data. It can be more efficient than standard vector-based models when the training sample is small or the inputs are matrices, since this model has less parameters than standard ones and exploits an inner structure of the inputs)