非负性约束条件下的系统辨识研究

项目名称： 非负性约束条件下的系统辨识研究

项目编号： No.61471251

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 无线电电子学、电信技术

项目作者： 倪锦根

作者单位： 苏州大学

项目金额： 81万元

中文摘要： 自适应滤波技术在系统辨识中具有广泛的应用。由于受系统固有物理特性的限制，一些待辨识系统的最优估计系数向量需要受到非负性条件的约束。为了解决非负性约束条件下的系统辨识问题，研究人员提出了非负自适应滤波的概念，并在Karush-Kuhn-Tucker条件基础上推出了非负最小均方算法。为了提高非负自适应滤波的收敛性能和扩展非负自适应滤波的应用范围，本项目拟对如下四个方面进行研究：1)分别采用数据重用和子带分割的方法来白化输入信号，使得自适应滤波器的系数向量在白噪声和相关信号输入下都收敛到相同的非负最优值；2）采用L0范数优化的方法来加快非负自适应滤波的收敛速度；3）建立非负性约束条件下的二维系统辨识方法；4)建立基于分布式网络的非负自适应滤波方法。通过本项目的研究，有望形成较完整的非负性约束条件下的系统辨识理论，为非负自适应滤波方法在不同领域中的应用提供理论依据和方法指导。

中文关键词： 自适应信号处理；系统辨识

英文摘要： Adaptive filtering techniques have been widely used in system identification. Due to the inherent physical characteristics of some systems under investigation, nonnegativity is a desired constraint that is imposed on the optimal estimated coefficient vector of the systems. In order to address the problem of system identification with nonnegativity constraints, some researchers have proposed the concept of nonnegative adaptive filtering and have derived the nonnegative least mean square (NNLMS) algorithm based on the Karush-Kuhn-Tucker conditions. To improve the performance of nonnegative adaptive filtering and to extend the application scope of nonnegative adaptive filtering, this project plans to study the following four aspects: 1) using the methods of data reusing and subband partitioning, respectively, to whiten input signals so that the coefficient vector of the adaptive filter can converge to the identical nonnegative optimal value for both white and correlated input signals; 2) using the L0-norm optimization method to increase the convergence rate of nonnegative adaptive filtering; 3) developing the method of two-dimensional system identification with nonnegativity constraints; 4) developing the method of nonnegative adaptive filtering over distributed networks. Through the study of this project, it is expected to form a relatively complete theory of system identification with nonnegativity constraints and to provide theory evidence and method guidance for the application of nonnegative adaptive filtering in varoius fields.

英文关键词： Adaptive signal processing;system identification