kmeans

this is a matlab file for modified yule nielsen model for predicting the printed area color

laundress using stateflow code in matlab

Generates a pulse with length Tp ,which is composed of Nc cycles of a sinusoidal waveform sinpulse is the waveform representing the pulse

M序列信号算法仿真在系统辨识中有着很大的应用前景。多谐差相方法辨识精度很高有着很苛刻的要求，要求已知辨识参数个数已知并且需要整周截断。而M序列信号的测试方法没有这个方面的要求。其辨识未知模型时，可以用最小二乘算法观察辨识系统的精度来确定模型的阶次。本算法里面不但给出了用于M序列生成的本原多项式计算方法，同时编写了M序列信号的生成算法，并编写了相关辨识方法的算法。(M sequence signal simulation algorithm for identification in the system have great application prospects. Identification of multi-harmonic differential phase method with high precision has very stringent requirements, demand parameters are known to identify the number of known and need to cut off the whole week. The M sequence signal testing methods do not have this requirements. Its identification unknown model, you can observe the identification system using least-squares algorithm to determine the accuracy of the model order times. This algorithm is used which not only gives the M sequence generated by primitive polynomial method of calculation as well as prepare the M sequence signal generation algorithm, and the preparation of the relevant identification method algorithms.)

说明：  小波插值（全小波插值，小波双线性插值，小波双三次插值及其改进）放大图像，提高图像的分辨率；对插值图像做质量评价（峰值信噪比PSNR；均方信噪比SNR）(Wavelet interpolation (full wavelet interpolation, wavelet bilinear interpolation, cubic interpolation and improved method) to enlarge the image and improve image resolution assesse the interpolation image (peak signal to noise ratio PSNR mean square signal to noise ratio SNR))

MATLAB通信仿真及应用实例 很不错的 老师竭力推荐(on demand)

运用FDTD法，使用C语言计算二维TM波时谐场相位人图的程序.(Using FDTD method, using the C language to calculate the two-dimensional TM wave the harmonic field phase program.)

MATLAB 辛苦攒下的十大经典算法，这是M源码。(MATLAB algorithms classic source)

此函数用于产生脉冲超宽带系统的训练序列的波形。输出参数有三个：bits--发送的数据,stx--发送的信号,ref--参考信号 发送端调制方式为TH-PAM(The emerging ultra-wideband (UWB) system offers a great potential for high data rate wireless multimedia applications of the home entertainment and industry, as well as for low data rate sensor networks involving low power devices~cite{paragraph1}. One of the most acute challenges in realizing these potentials of the UWB systems is the timing acquisition. Timing errors as small as fractions of a nanosecond could seriously degrade the system performance~cite{paragraph21}. The difficulty in UWB synchronization arises from UWB signals being the ultrashort low-duty-cycle pulses operating at very low power density.)

adaptive MMSE equalizer