基于系统参数化理论的信号稀疏表示和观测系统优化设计

项目名称： 基于系统参数化理论的信号稀疏表示和观测系统优化设计

项目编号： No.61304124

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 自动化技术、计算机技术

项目作者： 常丽萍

作者单位： 浙江工业大学

项目金额： 23万元

中文摘要： 压缩感知理论以一种新的采样框架突破了传统的数字信号采样方式，为缓解人们对巨量信息的需求压力提供了一种全新的方法。其中，信号稀疏表示和非相干观测直接影响着感知的效率，而目前研究成果对信号稀疏表示中的分析模型仍缺乏深入的理论探讨，尤其是信号字典无法做到与信号自适应。本项目旨在针对该关键问题提出一种新型信号字典设计方法并构建非相干观测系统，具体研究内容包括：1)基于信号建模、系统结构理论和优化算法，建立信号、系统参数和稀疏系数三者之间的优化模型，以最优系统结构参数设计信号字典，实现信号-字典间自适应；2)基于紧框架理论和梯度算法，构建字典优化下的非相干观测系统，明确字典和观测矩阵对高概率重构信号的影响机制；3)在此基础上，构建语音处理应用框架，实现稀疏表示分析模型在CS系统中的语音重构和消噪。本项目研究工作将为音频、图像、无线网络等应用领域提供重要理论依据和应用价值。

中文关键词： 压缩感知；稀疏字典；观测矩阵；优化算法；

英文摘要： Compressed sensing is a novel sampling framework which has broken through the traditional signal samping mode and provided a new method to alleviate the pressure of demand for the huge amounts of information. Therein, signal sparse representaion and incoherent measurement are the key to the success of the CS techniques. However so far the analysis model is lack of in-depth research and the dictionary is not adaptive the signal characteristics. In this project, aiming at these key problems, a new dictionary design concept is proposed and a novel incoherent measurement system is investigated. Firstly, the optimization model between the signal, system parameters and sparse coefficients is proposed with the help of the theories of signal modeling, system structures and optimization techniques. The signal-adapted dictionary is realized by the structure parameters of the optimal system. Secondly, an incoherent measurement system is designed for the given dictionary based on the tight frame theory and gradient algorithm. And the infulence of the dictionary and projection matrix on the signal reconstuction with high probability will be studied profundly. At last, as applications, the speech proccesing CS system is exploited for the speech reconstruction and denoising using the analysis model. The outcomes of this projec

英文关键词： compressed sensing；sparsifying dictionary；sensing matrix；optimization algorithm；