eetop.cn_FYP_V2

模式识别中朴素贝叶斯分类器,实习数据的良好分类技术(naive bayesian classification)

自行编程，采用有限差分法，求解画出微带线电场线分布图。注释详细(Own programming, using the finite difference method, seeking microstrip line power line distribution.)

傅里叶变换，用于故障诊断时候的频谱分析，压缩文件中包含一个word文档，用于分析电机故障中的电流中的噪声频谱。(FFT is commonly used to analyse fault diagnosis, especially when dealing with machine faults)

Histogram equalization. Is a method in image processing of contrast adjustment using the image s histogram. This method increase the contrast of the example s image, because it s a image represented by close contrast values.

图像校准的测试图片。标准的棋盘图像。摄像机标定。(Image calibration test image. Standard chessboard image. Camera calibration.)

用DFT对离散信号进行谱分析,通过选用不同的加窗函数来抑制信号截断造成的频谱泄漏(DFT of a discrete signal spectrum analysis, by choosing different windowing functions to suppress the spectral leakage caused by the signal cut)

最近交互式电源技术，软交换、同步整流、频率固定(Alternating expressions Power technology recently、Softswitch, synchronous rectification, fixed frequency)

常用的MATLAB插值算法，包括高斯，牛顿插值等等(Interpolation algorithm commonly used)

放在matlab里运行，可以演奏《kiss the rain》嘿嘿嘿~ 今天看到有大神用matlab弹奏卡农，我好激动呀，于是。。。（感谢XBC童鞋提出的建议，《kiss the rain》,话说这个曲子好难啊。。。）我鼓捣了一个下午，在前面这个牛程序的基础上，修改了好久（无数次维数出错，以及其他不易察觉的小问题），终于把《kiss the rain》的曲子鼓捣出来了。。。。。。 因为使用的是简谱，而且这首曲子的音域实在太宽了（从下面打三点的到上面打三点的都有，虽然可以编写出程序。。。但是太痛苦了啊。。。）,所以第二声部的有很多我都没有按照原本的谱子来编程，不过这也算一种再创作了哈？~【你明明就是偷懒啊喂】大家随便听听就好，如果有制作其他曲子的建议也欢迎提出哈，等我考完试做完功课写完材料【未知的某个世纪】就可以多做一些了~ 其实程序的原理我还一知半解【CANON的制作者牛掰惨了啊~】，只知道大概就是频率啊周期啊神马的，但是这对制作曲子的影响不大，大家有兴趣也可以做呀，除了眼睛有点花以外。。。真心是特别有趣呢~~~ 对了，有些语句是可以去除的，只不过我没有删，对运行是没有影响的哈~ (It can play KISS THE RAIN song)

In this work, the Mel frequency Cepstrum Coefficient (MFCC) feature has been used for designing a text dependent speaker identification system. The extracted speech features (MFCC’s) of a speaker are quantized to a number of centroids using vector quantization algorithm. These centroids constitute the codebook of that speaker. MFCC’s are calculated in training phase and again in testing phase. Speakers uttered same words once in a training session and once in a testing session later. The Euclidean distance between the MFCC’s of each speaker in training phase to the centroids of individual speaker in testing phase is measured and the speaker is identified according to the minimum Euclidean distance. The code is developed in the MATLAB environment and performs the identification satisfactorily.