2-D adaptive State-Space Filters and Their Applications

对二维(2-D)自适应状态空间滤波器及其应用进行了研究，得到了以下结果：1.利用Roesser局部状态空间(LSS)模型和最小均方(LMS)算法，提出了一种设计2-D(3-D)自适应状态空间滤波器的算法。2.为了减少运算量，提出了一种二维(3-D)可分离分母形式的自适应算法。3.研究了基于二维(3-D)状态空间滤波器并行实现的自适应算法。4.利用Roesser LSS模型在频域考虑了一种自适应算法。5.利用Fornasini-Marchesini第二LSS模型和LMS算法设计了2-D自适应状态空间滤波器。6.上述2-D自适应状态空间滤波器已被应用于图像降噪和2-D系统辨识。

A study on the two-dimensional (2-D) adaptive state-space filters and their applications has been carried out and we have obtained the following results :1.An algorithm for designing 2-D (3-D) adaptive state-space filters has been developed by using the Roesser local state-space (LSS) model and the least mean square (LMS) algorithm.2.To reduce its computational burden, an adaptive algorithm has been introduced in a 2-D (3-D) separable-denominator form.3.An adaptive algorithm based on the parallel-form realization of 2-D (3-D) state-space filters has been investigated.4.An adaptive algorithm has been considered in the fequency domain by using the Roesser LSS model.5.The Fornasini-Marchesini second LSS model and the LMS algorithm have been used to design 2-D adaptive state-space filters.6.The 2-D adaptive state-space filters mentioned above have been applied to both noise reduction of an image and 2-D system identification.