twodimentrls

classifier ID3 to classify data

简单的K均值聚类函数，用于求算重心的函数，算法高效快速(Simple K-means clustering function for calculating the center of gravity function, the algorithm is fast and efficient)

这是SAR成像点目标仿真中的wK算法，程序严格按照Ian G. Cumming的《合成孔径雷达成像算法与算法》中wK算法来编写，对于学习wK算法的同学来说是入门级的仿真程序 (This is the the SAR imaging point target simulation the wK algorithm, the program written in strict accordance with the Ian G. Cumming synthetic aperture radar imaging algorithm and algorithm wK algorithm for students learning wK algorithm is entry-level simulation program)

课程设计中首先采用Ising model的思想建立一个二维的模型，然后利用重要性抽样和Monte Carlo方法及其思想模拟铁磁-顺磁相变过程。计算了顺磁物质的能量平均值Ev、热容Cv、磁化强度M及磁化率X的值，进而研究Ev、Cv、M、X与温度T的变化关系并绘制成Ev-T图、Cv-T图、M-T图、X-T图，得出顺磁物质的内能随着温度的升高先增大而后趋于稳定值；热容Cv、磁化率X随着温度的升高先增大后减小；磁化强度M在转变温度Tc处迅速减小为零，找出铁磁相变的转变温度Tc大约为2.35(First of all, curriculum design idea of the Ising model used to establish a two-dimensional model, the importance of sampling and then use Monte Carlo simulation methods and their idea of ferromagnetic- paramagnetic phase transition process. Paramagnetic material calculated average energy Ev, heat capacity Cv, magnetization M and susceptibility X value, and then study Ev, Cv, M, X and temperature changes in the relationship between T and plotted into Ev-T map, Cv- T diagram, MT map, XT maps drawn paramagnetic material can be increased as the temperature increased and then stabilized value heat capacity Cv, magnetic susceptibility X as the temperature increases after the first minus small magnetization M in the transition temperature Tc decreases rapidly to zero Department to identify ferromagnetic phase transition around the transition temperature Tc for 2.35)

本文简单介绍了matlab神经网络工具箱应用并附有例子(This article explains the application of neural network toolbox matlab together with examples)

三种方法实现数字下变频：直接法、bessel插值、多相滤波等(three method of DDC)

艾肯特插值，高斯插值和牛顿插值法的matlab代码。上述三种方法均用于数值插值。(Ai Kente interpolation, the matlab code of the the Gaussian interpolation and the Newton interpolation law. The the above-mentioned three methods are used for the numerical interpolation.)

自组织特征映射模型(Self-Organizing feature Map)，认为一个神经网络接受外界输入模式时，将会分为不同的区域，各区域对输入模式具有不同的响应特征，同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激，而较远的神经元则相互抑制，更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。(Self-organizing maps model (Self-Organizing feature Map), that a neural network to accept outside input mode, will be divided into different regions, the regional input modes have different response characteristics, while the process is done automatically . The connection weights of neurons with a certain distribution. Nearest neurons stimulate each other, while distant neurons are mutually inhibitory, with a further some of the weaker stimulus. Self-organizing feature map method is a clustering method without teachers.)

能够很准确的计算单输入单输出系统的信噪比。(Very accurate calculation of the SNR of the single-input single-output system.)

OFDM-MIMO收发系统，The simulator GUI is started with command ui_start in Matlab command window.-,matlab,通讯编程/Communication(OFDM-MIMO transceiver system, The simulator, GUI is started with command ui_st art in Matlab command window .-, Matlab, Communication Programming/Communication)