QOSTBC

GS算法的matlab例子，本例子仿真了一个圆形的光环结构，其它的参数见matlab中的注释(GS algorithm matlab example, the example of simulation of a circular ring structure, and other parameters, see the Notes matlab)

这是matlab用户手册，对于初学者很有益，里面涉及到各个方面，很有价值的参考资料。(This is a matlab user manual, very useful for beginners, which relate to various aspects valuable reference.)

过程工业中带有粘滞的阀门数据驱动模型，模型采用SCI论文《Two-layer banary tree data-driven model for valve stiction》中提出的算法，本人自己独立编制转化，成功运行，性能良好。模型由Matlab文件和Simulink模型两部分完成，且内设注释，可直接运行。(A data-driven model of valve stiction. The algorithm is from the paper"Two-layer banary tree data-driven model for valve stiction," and the model runs successfully in MATLAB/SIMULINK.)

信号频谱绘制函数，绘制输入输出函数，并计算信号的sndr。(Signal spectrum drawing functions to draw input and output functions, and calculate sndr signal.)

本实验语音库为免费的柏林情感语音库，其采样频率为16KHZ，16bit量化。该语音库共有500 句情感语音信号，分别由十名专业演员(5 男，5 女)在不同情感状态下（高兴、愤怒、平静、悲伤、害怕、厌烦、憎恨）朗读十句不同文本的德语组成。本实验选取其中的部分情感（高兴、愤怒、悲伤）加以识别。仿真实验环境为MATLAB7.0。 实验选取的情感特征为短时平均能量、短时平均幅度、基频和短时过零率。为了降低不同人在表达不同情感时的个人差异造成的影响，本文实验过程中将提取的情感特征进行归一化处理。归一化采取将同一个人的三种情感语音信号的情感特征放在一起归一化处理，并将归一化后的情感特征作为KNN分类器的训练样本和测试样本。 该实验使用了传统的KNN算法和改进算法两种识别方式，通过实验结果对比了各自的特点。 (This experiment YuYinKu for free Berlin YuYinKu emotion, the sampling frequency for 16 KHZ, 16 bit quantification. The YuYinKu 500 words of emotional speech signal, respectively by ten professional actors (5 male, five female) in different emotional state (happy, anger, sadness, fear, calm, bored, hate) read ten sentences in different text of the German. This experiment selection of part of the emotions (joy, anger, sadness) is recognized. The simulation experiment environment for MATLAB7.0. The selection of emotional characteristics for short-term average energy, short-term average amplitude, frequency, and the short zero rate. In order to reduce the different people in different emotional expression of the impact of individual differences, the experiment process will extract emotional characteristics is normalized. The normalized will take the same three kind of emotional speech signal emotional features normalized put together, and after the normalized the emotional characteristics)

报童问题(负指数分布) 几个参数： 卖出报纸挣a元，退回报纸赔b元 卖报量y,订报量z，订报量上限z_up 观察期的总天数t,用于积累天数的ti 总的平均损失量ave_loss，供过于求损失loss1,供小于求损失loss2,ave_loss=loss1+loss2 最佳订报量superz,最小损失量ave_loss_min (newsvender)

说明：  求解LE，小数据量法，简单易操作。。。。(Solving the LE, the small amount of data law)

信息论与编码中，对香农信源编码定理的仿真，验证了香农编码定理的可行性。(information theory and coding, right Shannon source coding theorem simulation, verification of the Shannon coding theorem.)

牛顿插值和三次样条插值的matlab实现(Newton interpolation and cubic spline interpolation)

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