Solar-Thermal

基于Matlab的三阶魔方模拟软件，操作简单，初学者试编程序，仅供参考。(The third-order cube based on Matlab simulation software, simple operation, a trial program for beginners, for reference only.)

Subject of this thesis is elemental description of DVB digital television and digitalization process of its terrestrial transmission according to DVB-T standard. The thesis characterizes in detail RF transmission channels used for wireless distribute of television. These channels ale mathematically described and their effect to OFDM signal is simulated in the MATLAB environment.

本文研究了模糊系统和神经网络这两种人工智能方法的长处和短处，并将它们有机地结合在一起。将基于T-S模型的模糊神经网络应用于水质评价中，取得了较好的效果，为水质评价提供了一个新的方法。 (In this paper, fuzzy systems and neural network artificial intelligence methods both strengths and weaknesses, and they are organically combined. TS model based fuzzy neural network used in water quality assessment, and achieved good results for water quality assessment provides a new approach.)

使用1749年至1924年太阳黑子的经典序列来确定和估计具有观测误差的模型(specification and estimation of models with observation errors using W?lfer’s classic time series of total number of sunspots from 1749 to 1924)

home work: PSLR, ISLR

雷达基础导论，雷达监测，雷达波形，雷达模糊函数，脉冲压缩，面杂波与体杂波，动目标显示和杂波抑制，相控阵，目标跟踪，电子对抗，雷达截面积，高分辨率战术合成孔径雷达，信号处理。(MATLAB Simulation for Radar System Design)

短时傅里叶变换的Matlab程序代码，短时傅里叶变换时最经典的时频分析方法(Matlab code short time Fourier transform, short-time Fourier transform of the most classic time-frequency analysis)

用MATLAB编写的RBF神经网络程序，能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性.(Using MATLAB RBF neural network program that can approximate any nonlinear function that can handle difficult analytic regularity within the system.)

这个是基于局部空间信息的模糊聚类的算法，用于图像聚类，希望对大家有点帮助(This is based on fuzzy clustering algorithm partial spatial information for image clustering, hope to help a bit)

《MATLAB神经网络30个案例分析》中的第24个例子，案例24 模糊神经网络的预测算法-嘉陵江水质评价。希望对大家有一定的帮助！(The MATLAB neural network analysis of 30 cases of 24 example, 24 cases of fuzzy neural network prediction algorithm- jialing river water quality assessment. Hope to have certain help to everybody! )