CirclesIntersection

用Matlab以及c语言求语音序列的倒谱 这某段语音信号求FFT、取模、取log、IFFT得到倒谱，并画图。选取一段进行分析，分别对浊音和清音各自求倒谱。(Using Matlab, as well as for c language serial Cepstral voice that voice signal for a certain period of FFT, check mode, check log, IFFT been cepstrum, and drawing. Select a section of the analysis, respectively, and the voiceless to voiced their demand cepstrum.)

通信原理实验中的数字调制部分二进制频率调制(Communication theory experiment in digital modulation part of the binary frequency modulation)

It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems. The emphasis is on models for both identification and control. Static and dynamic backpropagation methods for the adjustment of parameters are discussed. In the models that are introduced, multilayer and recurrent networks are interconnected in novel configurations, and hence there is a real need to study them in a unified fashion. Simulation results reveal that the identification and adaptive control schemes suggested are practically feasible. Basic concepts and definitions are introduced throughout, and theoretical questions that have to be addressed are also described

这是MosaicKit的matlab程序，可以用于图像融合等(This is the Matlab MosaicKit procedures can be used for image fusion, etc.)

牛顿迭代法的matlab编写，以及matlab数值方法中的案例编写(Newton iterative method to write matlab)

在Matlab对FDTD进行仿真，并对一维，二维及三维电磁传播环境分别编写了程序(On the FDTD simulation in Matlab, and the one-dimensional, two-dimensional and three-dimensional electromagnetic propagation environment programs were prepared)

程佩青版数字信号处理部分作业的matlab程序... 只做过了老师布置的题目. (Cheng Peiqing version of digital signal processing operations matlab program ... )

matlab 计算框架结构模态，频域法计算(matlab calculate frame mode, frequency-domain method to calculate)

本程序是雷达SAR图像算法的经典程序集合，包含波数域算法，RD算法和CS算法，对于学习SAR成像非常有帮助(This procedure is a SAR radar image of the classic algorithm collection procedures, including the wave number domain algorithm, RD algorithm and CS algorithm for SAR imaging study very helpful)

说明：  Regression sum of squares , the maximum deviation , minimum deviation , the average deviation