autocorrelazione

编写matlab程序，仿真2DPSK调制信号在高斯信道下分别采用相干解调及差分相干解调两种解调方式时的性能，并与理论分析结果相比较。(Write matlab procedures, simulation 2DPSK modulated signals in Gaussian channel performance respectively coherent demodulation and coherent demodulation difference when the two demodulation, and compared with the theoretical analysis.)

求取倒频谱系数，可对声音信号进行分析，是一种特征提取方式(Obtaining cepstral coefficients, can the sound signal analysis, feature extraction is a way)

Orbital calculation for satellite communication GUI in MATLAB

根据2FSK调制器与解调器的组成原理，设计出整个2FSK传输系统的实现方案与电路(Based on composition theory 2FSK modulator and demodulator, the entire design implementation and circuit transmission system 2FSK)

一维小波变换对信号进行去噪，小波包变换，对地震记录进行去噪(A one-dimensional wavelet transform for signal denoising, wavelet packet transform, the noise of seismic record)

主成分分析是把原来多个变量划为少数几个综合指标的一种统计分析方法。 从数学角度来看，这是一种降维处理技术。(Principal component analysis (PCA) is a statistical analysis method that divides a number of variables into a few comprehensive indexes.From a mathematical point of view, this is a kind of dimensionality reduction technology.)

神经计算的MATLAB教程，包含常用算法实现及其原理，BP/HEBBIAN/SMO等等，神经计算专用(The MATLAB neural computing tutorials, including the commonly used algorithm, BP/HEBBIAN/SMO, etc., etc., dedicated neural computing)

主成分分析 还不错的程序 有需要的可以试试(pca for zhe value)

利用朴实贝叶斯方法求解有关肺炎的问题。肺炎对应有四个特征：发烧、疼痛、咳嗽和血细胞异常，当确定了患肺炎与否时，四个特征条件独立。假设患肺炎与否和四个特征都可表示为Ture和False。 根据pneumonia.tex文件中的数据（500行，每行前4个数对应4个特征变量，第5个数对应患肺炎是否为真，以0表示False，1表示Ture），编写Matlab 程序 maininference.m，从example.txt中读取病人的症状信息（0表示False，1表示True，-1表示not given），并计算对应的患肺炎的可能性。所给的信息按发烧、疼痛、咳嗽、血细胞异常的顺序排列。将计算结果保存在answer.txt中。(Simple Bayesian method to solve the question of pneumonia. Pneumonia corresponding four characteristics: fever, pain, cough and blood cell abnormalities, determine the risk of pneumonia or not, the four characteristics of conditional independence. Assumptions suffering from pneumonia or not and four features can be represented as Ture and False. According to the data pneumonia.tex file (500 lines, each line of the first four numbers corresponding to the four characteristic variables, number 5 corresponds to the risk of pneumonia is true, 0 represents False, said Ture), to write Matlab program maininference. m from example.txt read the information of the patient' s symptoms (0 = False, said True, the-1 indicates not given), and to calculate corresponding to the likelihood of suffering from pneumonia. The information given by the order of fever, pain, cough, blood cell abnormalities. The calculated results is be saved in answer.txt.)

科学计算与MATLAB语言科学计算与MATLAB语言(Scientific Computing with MATLAB and the MATLAB language of scientific computing language)