SVDwatermark

说明：  一维小波分析对平稳信号消噪 One-dimensional wavelet analysis on the stationary signal denoising一维小波分析对平稳信号消噪 One-dimensional wavelet analysis on the stationary signal denoising

MATLAB读写裸数据，将MATLAB的mat格式文件，写成所需的图像类型格式(MATLAB to read and write raw data to the MATLAB mat format file, write the desired image type format)

说明：  讲述了灌型CT的工作原理和过程，具有重要的意义(Describes the working principle of irrigation-based CT and process of great significance)

用于结构在动力荷载作用下的时程分析,地震荷载，随即荷载均可，采用newmark方法(For structural time history analysis under dynamic loads, seismic loading, then the load can be, using the newmark method)

一个地震正演程序,matlab源码,对相关专业的初学者有帮助。(a seismic forward procedures, Matlab source of relevant professional help beginners.)

微分方程求解，利用matlab软件，解决微分方程领域各种问题(Solving differential equations using matlab software, field problems to solve differential equations)

信号时域采样,频域进行频谱分析matlab，适合初学者。(signal analytic)

mRMR(min-redundancy max-relevance)的matlab程序(matlab program of mRMR(min-redundancy max-relevance))

这是一个利用自相关函数以及中心肖波算法求取基音频率的程序，其基于MATLAB。(it is a program about get pitch.it based on MATLAB)

本实验语音库为免费的柏林情感语音库，其采样频率为16KHZ，16bit量化。该语音库共有500 句情感语音信号，分别由十名专业演员(5 男，5 女)在不同情感状态下（高兴、愤怒、平静、悲伤、害怕、厌烦、憎恨）朗读十句不同文本的德语组成。本实验选取其中的部分情感（高兴、愤怒、悲伤）加以识别。仿真实验环境为MATLAB7.0。 实验选取的情感特征为短时平均能量、短时平均幅度、基频和短时过零率。为了降低不同人在表达不同情感时的个人差异造成的影响，本文实验过程中将提取的情感特征进行归一化处理。归一化采取将同一个人的三种情感语音信号的情感特征放在一起归一化处理，并将归一化后的情感特征作为KNN分类器的训练样本和测试样本。 该实验使用了传统的KNN算法和改进算法两种识别方式，通过实验结果对比了各自的特点。 (This experiment YuYinKu for free Berlin YuYinKu emotion, the sampling frequency for 16 KHZ, 16 bit quantification. The YuYinKu 500 words of emotional speech signal, respectively by ten professional actors (5 male, five female) in different emotional state (happy, anger, sadness, fear, calm, bored, hate) read ten sentences in different text of the German. This experiment selection of part of the emotions (joy, anger, sadness) is recognized. The simulation experiment environment for MATLAB7.0. The selection of emotional characteristics for short-term average energy, short-term average amplitude, frequency, and the short zero rate. In order to reduce the different people in different emotional expression of the impact of individual differences, the experiment process will extract emotional characteristics is normalized. The normalized will take the same three kind of emotional speech signal emotional features normalized put together, and after the normalized the emotional characteristics)