通信信号调制识别中的分类器设计大学毕业设计.doc

毕 业 论 文（设 计） 题 目： 通信信号调制识别中的分类器设计 英文题目：Classifier Design Recognition of Modulation of Communication Signals 院 系： 电子工程学院 专 业： 通信工程 姓 名： 年 级： 指导教师： 年月 。 调制信号识别普遍应用于信号区分、干扰识别等多种领域。神经网络是一种模拟生物神经工作的方法，功能与人脑有某些相似之处，具有自学习和存储功能，算法具有智能性，对于处理非线性问题很有用处，并且广泛用于现在各个领域，例如做销售量的非线性预测，计算机智能控制，图像的处理，优化算法方面等等。在先辈们的基础之下，更深层次的研究信号识别问题。具体工作如下： 概述了一些常见的调制信号给出一些经常使用调制信号的数学原型，考察了数字调制信号的一些基本特性，如时域波形和频谱图。 对神经网络分类器作整体的介绍。 研究了分类器的训练算法，并对传统的BP网络的不足提出改进算法。仿真实验表明，将提取的时频分析特征通过改进的 BP 神经网络分类器进行分类，实现了不单一的信号在较大信噪比变化范围内的自动识别，期望的结果。 关键词： 调制识别；时频特征；神经网络  Classifier Design Recognition of Modulation of Communication Signals Abstract Modulation recognition of communication signals is one of the key technologies in communication reconnaissance, is an important task in the field of electronic warfare. In this paper, aiming at the problem of communication signalmodulation recognition, in-depth study of the signal feature extraction method,on the basis of the design method of classifier. Modulation recognition is widely usedin signal distinction, interference identification and other fields. Its purpose is in a complex environment with noise conditions, in the absence of a priori knowledge, are processed by the reception of the signals, then judge the modulation signal. Neural network is a method of simulation of biological neural work, has some similarities with the human brain function, self learning and memory function,algorithm is intelligent, very useful for dealing with nonlinear problems, and fornow in various fields, such as nonlinear do sales forecasting, computer intelligent control, image processing, optimization algorithm and so on. Based on the predecessors, the research of signal recognition deeper problems. The specific work is as follows: 1, an overview ofsome common signal modulation. Some frequently usedmodulation signal mathematical prototype, investigate so