BLDC

数学建模初步与MATLAB等工具软件简介(matlab)

说明：  里面有不少MATLAB学习课件,对新手很有帮助。(there are many study matiarial)

散傅里叶变换的性质 一、 实验目的 1、 掌握离散傅里叶变换的性质，包括线性特性、时移特性、频移特性、对称性和循环卷积等性质； 2、 通过编程验证傅里叶变换的性质，加强对傅里叶变换性质的认识。 (The nature of the discrete Fourier transform, the purpose of the experiment 1, to grasp the nature of the discrete Fourier transform, including a linear characteristic, when the shift characteristic frequency-shift characteristic, symmetry, and the circular convolution nature 2, through the programming verification Fu li the nature of the Fourier transform, to enhance the understanding of the nature of the Fourier transform.)

nose cancellation releted

地震资料处理，时频分析里的wiggle变换(Seismic data processing, time-frequency analysis in the transform wiggle)

用于产生多相编码序列P1码以及对产生的码字进行匹配脉压(generate P1 code and let the code throngh the matched filter)

（7，4）系统循环码编码器 code_out = cyclic_coder(code_in) 该系统循环码编码器的生成多项式是g(x) = x^3 + x + 1 输入参数code_in是信息码字，是1×4的行向量；输出code_out是编码后的系统 循环码字，是1×7的行向量。 函数运行时，同时画出输入信息码字和循环码字的波形图。( (7,4) cyclic code system Encoder code_out = cyclic_coder (code_in) cyclic code encoder of the system generating polynomial is g (x) = x ^ 3+ x+ 1 of information input parameters code_in code word is 1 × 4 row vector output code_out System is encoded codeword cycle, the row is 1 × 7 vector. Function to run at the same time draw the input code word and code word cycle waveform.)

The early detection of arrhythmia is very important for the cardiac patients. This is done by analyzing the electrocardiogram (ECG) signals and extracting some features from them. These features can be used in the classification of different types of arrhythmias. In this paper, we present three different algorithms of features extraction: Fourier transform (FFT), Autoregressive modeling (AR), and Principal Component Analysis (PCA). The used classifier will be Artificial Neural Networks (ANN). We observed that the system that depends on the PCA features give the highest accuracy. The proposed techniques deal with the whole 3 second intervals of the training and testing data. We reached the accuracy of 92.7083 compared to 84.4 for the reference that work on a similar data.

SMI算法的一些源程序，简单的指出了期望信号协方差矩阵，干扰信号协方差矩阵，噪声信号协方差矩阵。(Some of the source of the SMI algorithm, simply that the desired signal covariance matrix, the covariance matrix of an interference signal, the noise signal covariance matrix.)

PHOTOVOLTAIC MODELISATION WITH SIMULINK