TP1_CHEN

Visual C++ Huffman Map Implementation

本文针对当前科技水平不足以有效存储电力的情况下产生的发电机机组组合的问题，考虑负荷平衡、输电线传输容量限制等实际情况产生的约束条件，建立机组组合优化模型，追求发电成本最小。同时采用矩阵实数编码遗传算法（MRCGA）和穷举搜索算法，利用MATLAB 7.0.1和C++编程，分别对模型进行求解，并对所得结果进行分析比较，以此来帮助电力部门制定机组启停计划(This article in view of the current level of science and technology would not effective storage power generator unit combination problem, considering the load balance, such as transmission line transmission capacity, the actual situation of constraint conditions, unit combination optimization model is set up, the pursuit of power generation cost minimum. At the same time using matrix real-coded genetic algorithm (MRCGA) and exhaustive search algorithm, using MATLAB 7.0.1 and c++ programming, the model is solved respectively, and analyzes and compares the results to help power unit start-stop planning department)

关于在MATLAB上产生DTMF信号以及对DTMF的监测(On MATLAB to generate DTMF signals and the monitoring of DTMF)

MAtlab file for Digital communication

用于多孔介质中波的传播，分析波的传播速度随入射角的变化，消除频散的特性(wave propogation in porous media)

说明：  通过此程序实现对微装配的调用微动平台的实现(Achieve through this process called micro-assembly platform for the realization of micro-)

数字信号处理－理论、算法与实现 一书中所涉及到的绝大部分算法。 Dsp_c C语言编写的算法程序。 Dsp_fortran FORTRAN语言编写的算法程序。 Dsp_matlab用MATLAB编写的信号处理程序，包含本书各个章节的 大部分例题。(" Digital Signal Processing- Theory, Algorithm and Implementation of a book related to most of the algorithm. The DSP_C C language algorithm. Dsp_fortran FORTRAN language written algorithm. Dsp_matlab prepared using MATLAB signal processing procedures, including most of the examples of the various chapters of the book.)

说明：  图象压缩方面的论文pdf格式 可用于毕业设计方面的工作(Image compression pdf format papers for school design work)

屬於SUGENO模糊模型可以藉由類神經網路架構來替代(Belonging to fuzzy model can SUGENO neural network architecture to replace)

说明：  按FPE定阶的 源程序：fpe.cpp M序列：M序列.txt 白噪声：Gauss.txt 程序中先用依模型阶次递推算法估计模型的参数，再用fpe方法判断模型的阶次。 程序运行结果如下： n: 1 判断阶次FPE的值: 0.0096406 -0.481665 1.07868 n: 2 判断阶次FPE的值: 0.00875755 -0.446739 0.00498181 1.07791 0.0527289 n: 3 判断阶次FPE的值: 0.0087098 -0.459433 0.120972 -0.0569228 1.07814 0.0390757 0.116982 n: 4 判断阶次FPE的值: 0.000396884 -0.509677 0.4501 -0.200906 0.0656188 1.07991 -0.0156362 0.442989 0.0497236 n: 5 判断阶次FPE的值: 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771 n: 6 判断阶次FPE的值: 3.23349e-007 -1.14659 0.76933 -0.487651 0.329676 -0.10377 -0.00440907 1.07999 -0.703574 0.447253 -0.235282 0.113587 0.00479688 从以上结果可以看出，当n=5时，fpe值最小，所以这时的模型阶次和参数估计值为最优结果： 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771(err)