无线通信环境的多样性和复杂性对自适应滤波性能提出了前所未有的挑战。项目针对目前实现自适应滤波结构的各类算法在复杂度、鲁棒性、收敛性和失调量等性能经常不相容而需要权衡的问题，以平衡实现算法为研究对象，研究离散时间系统参数结构化、平衡实现结构的系统状态空间方程和系统传递函数、自适应滤波器性能优化等内容，分析不同的参数构造对系统结构和稳定性带来的影响。项目预期实现参数迭代过程中使系统稳定保持平衡状态的方法，分别用系统传递函数和状态空间方程的方式建立直接基于离散时间系统的平衡实现自适应IIR滤波结构，并采用平衡截断较大奇异值方法对系统进行了性能优化。项目研究成果拟解决平衡实现算法在自适应滤波结构上的研究难题，构建高性能自适应滤波器，对进一步拓展自适应滤波结构设计、系统辨识、信道均衡等理论的发展，为应对新时期无线通信技术发展带来的挑战具有重要的作用和意义。

The performance of adaptive filters is unprecedentedly challenged by the diversity and complexity of wireless communication environments. The project aims at solving an issue on existing algorithms that implement adaptive filtering structures: the performance specifications such as complexity, robustness, convergence and maladjustment, are inconsistent. Therefore trade-offs between these specifications are required. Targeting the balanced realization algorithm, the project investigates the structuring of the discrete-time system parameters, the system space state equations and transfer functions of the balanced realization structure, and the performance optimization of the adaptive filter. It also analyzes the influences on the system structure and stability caused by parameter differences. The project is expected to achieve a method that steadily keeps the system balance during parameter iterations. It also aims at founding a balanced realization adaptive IIR filtering structure by utilizing the system transfer functions and the space state equations respectively based on a discrete-time system. Meanwhile, a system optimization method that evenly cuts-off greater singular values is proposed. The project solves the issue of applying the balanced realization algorithm on adaptive filtering structures, and builds a high-performance adaptive filter. The research supports further improvements in the areas of adaptive filtering design, system identification, and channel balancing. Furthermore, it helps to rise to the challenge of wireless communications in the new era.