sanfing_V6.3

通过改变想要处理的帧，和预测器阶数，对原始语音帧和预测语音帧作一个比较，并作出短时谱和lpc谱，最后作倒谱比较。(By changing the processing of the desired frame, and the predictor order, the original speech frame and the predicted speech frame to make a comparison and to make short-term spectrum and the lpc spectrum, cepstrum last for comparison.)

调频步进信号的产生matlab方式。希望有用！(generating step frequency signal use matlab!)

基于SVPWM的三电平逆变的matlab仿真，非常适合计算机视觉方面的研究使用,计算时间和二维直方图。( Based on SVPWM three-level inverter matlab simulation, Very suitable for the study using computer vision, Computing time and two-dimensional histogram.)

OFDR传感系统的建模仿真(Modeling and Simulation of OFDR sensing system)

gsl具有强大的矩阵运算，信号分析功能，使用gsl提供的库文件能加速vc开发复杂的数学运算，摆脱对MATLAB的依赖(gsl own powerful function of matrix operations and signal analysis , use the gsl provided library files,you can speed up the development of complex mathematical operations vc, get rid of dependence on the MATLAB)

matlab教程，比较入门级别的教程，从概念到语法，适合初学者。(matlab tutorials, more entry-level curricula, from concept to grammar, suitable for beginners.)

使用mat2huff进行编码，进一步说明霍夫曼编码的压缩性能！显示其压缩比例，以及其图像的对比！(Encoded using mat2huff to further clarify the Huffman coding compression performance! Shows the compression ratio and the image contrast!)

这是一基于MATLAB的复调制ZOOM-FFT的研究和实现的一篇文章，为的是提高频率分辨率。(This is a MATLAB-based complex modulation ZOOM- FFT Research and Implementation of an article, To improve the frequency resolution.)

Image Texture Classification Using Combined Grey Level Co-Occurrence Probabilities and Support Vector Machines Texture refers to properties that represent the surface or structure of an object and is defined as something consisting of mutually related elements. The main focus in this study is to do texture segmentation and classification for texture digital images. Grey level co-occurrence probabilities (GLCP) method is being used to extract features from texture image. Gaussian support vector machines (GSVM) have been proposed to do classification on the extracted features. A popular Brodatz texture album had been chosen to test out the result. In this study, a combined GLCP-GSVM shows an improvement over GLCP in terms of classification accuracy.

归一化的函数，神经网络的必须。希望对大家有用。。。。(Normalized function, neural networks have. Hope to be useful. . . .)