针对通信信号的非线性时域滤波问题，研究了量子随机滤波器的原理和性能。
Principles and performances of quantum stochastic filters are studied for nonlinear time-domain filtering of communication signals.
针对具有高斯噪声的非线性随机系统状态估计问题，提出了一种基于分段常值的贝叶斯状态估计滤波算法。
A filter algorithm of bayesian state estimation using piecewise constant was proposed for a nonlinear stochastic system with white noises.
针对离散随机动态系统的滤波问题，提出了基于信息融合估计的线性和非线性滤波方法。
The filtering methods based on information fusion estimation in linear or nonlinear systems was presented for the filtering problem in discrete dynamic stochastic system.
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