c3s1

主动控制悬架4自由度模型及控制算法，可以马上应用。(Active Control of 4-DOF suspension model and control algorithm can be applied immediately.)

说明：  用朴素贝叶斯方法实现了Iris数据的分类，还附了实验报告(Bayesian methods implemented with the Iris data classification, but also with the experimental report)

用于海杂波循环的对消的程序，能够很好地提高信噪比(For sea clutter cycle cancellation procedures)

本章对该文档的目的、功能范围、术语、相关文档、参考资料、版本更新进行说明。(The purpose of this chapter to the document, functional scope, terms, related documentation, reference materials, updated version will be described.)

匹配追踪和正交匹配追踪，采用偏最小二乘法，最小二乘回归分析算法。( Matching Pursuit and orthogonal matching pursuit, Partial least squares method, Least-squares regression analysis algorithm.)

时间跳变-脉冲位置调试超宽带发射和接收系统(TH-PPM ultra-wideband wireless communication system)

This program apply decimation on a speech file.

说明：  本程序在c平台下开发，描述了awng信道下QPSK调制的方针。结果较为理想(The program developed in c platform described awng channel QPSK modulation approach. More satisfactory results)

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)

matlab 最优化算法 matlab 最优化算法matlab 最优化算法matlab 最优化算法(matlab zuiyouhuasuanfamatlab zuiyouhuasuanfa matlab zuiyouhuasuanfa )