tiaozhi3

灰色模型在城市中长期用水量预测中的应用，近年来, 随着我国经济的飞速发展, 城市规模 不断扩张, 现有供水系统已经不能满足未来几年 的供水需求, 必须依照未来城市发展与城市布局 进行科学合理的供水系统规划. 在(Gray model in the application of long-term water demand in recent years, as China' s rapid economic development, urban-scale expansion, the existing water supply system can not meet the water needs of the next few years must be in accordance with future urban development and urban scientific and rational layout of the water supply system planning. In)

现代谱估计,用总体最小二乘法观测数据的ARMA模型的AR参数，并与一般最小二乘法进行比较。(Modern spectral estimation, total least squares method observational data of AR parameters of the ARMA model and compared with the general method of least squares.)

说明：  利用MATLAB编写控制系统的频域分析以及频率特性及其与时域响应的关系(Preparation of control systems using MATLAB in frequency domain analysis and frequency domain response characteristics and the relationship with the)

此为MATLAB简明教程，入门的话非常值得一看(This is a concise MATLAB tutorial and introductory words are worth a visit)

瑞利衰落信道下QAM信号的误码率和误比特率仿真程序(the Simbol error rate and Bit error rate of 16QAM signal over Rayleigh fading channel)

FEM for solving differential equation

说明：  通带滤波，用滤波法进行通带滤波，处理手段先进(tongdailvbo)

支持向量机的研究现已成为机器学习领域中的研究热点，其理论基础是Vapnik[3]等提出的统计学习理论。统计学习理论采用结构风险最小化准则，在最小化样本点误差的同时，缩小模型泛化误差的上界，即最小化模型的结构风险，从而提高了模型的泛化能力，这一优点在小样本学习中更为突出。SVM理论正是在这一基础上发展而来的，经过十几年的研究和发展，已开始逐步应用于一些领域。在解决小样本、非线性及高维模式识别问题中表现出许多特有的优势，已经在模式识别、函数逼近和概率密度估计等方面取得了良好的效果。( Support Vector Machine (SVM) is a new machine learning technique in recent years developed based on statistical learning theory (SLT). It wins popularity due to many attractive features and emphatically performance in the fields of nonlinear and high dimensional pattern recognition. The theory and algorithm of SVC is studied at first, then, simulation is to recognize handwritten numeral with the Lib-SVM toolbox. At last, we study the result, which shows that the SVC can do the classification problem with good performance, shorter operation time and is more suitable for real-time implementation.)

用优先级判断的处理器调度模拟程序，程序运行时间结束后结束。(Used to determine the priority of processor scheduling simulation program, after the close of the program is running.)

this is the model of power factor correction by matlab program