In this paper, we first give the concept of weakly P-inversive semigroup S（P）. Then we describe the strong P-congruences on S（P） in terms of their P-kernel normal systems. It is proved that there is a bijection be...In this paper, we first give the concept of weakly P-inversive semigroup S（P）. Then we describe the strong P-congruences on S（P） in terms of their P-kernel normal systems. It is proved that there is a bijection between the strong P-congruences and the P-kernel normal systems. Finally, it is also prove that the lattice of strong P-congruences and the lattice of P-kernel normal systems on S（P） are isomorphic.展开更多
Let S（P） be a P-inversive semigroup. In this paper we describe the strong P-congruences on S（P） in terms of their P-kernel normal systems. We prove that any strong P-congruence on S（P） can present a P-kernel nor...Let S（P） be a P-inversive semigroup. In this paper we describe the strong P-congruences on S（P） in terms of their P-kernel normal systems. We prove that any strong P-congruence on S（P） can present a P-kernel normal system; conversely any P-kernel normal system of S（P） can determine a strong P-congruence.展开更多
在强脉冲噪声干扰背景中,核递归最小二乘(Kernel Recursive Least Square,KRLS)算法和核递归最大相关熵(Kernel Recursive Maximum Correntropy,KRMC)算法对非线性信号预测性能严重退化,对此提出一种核递归最小平均P范数(Kernel Recursi...在强脉冲噪声干扰背景中,核递归最小二乘(Kernel Recursive Least Square,KRLS)算法和核递归最大相关熵(Kernel Recursive Maximum Correntropy,KRMC)算法对非线性信号预测性能严重退化,对此提出一种核递归最小平均P范数(Kernel Recursive Least Mean P-norm,KRLMP)算法。首先运用核方法将输入数据映射到再生核希尔伯特空间(Reproducing Kernnel Hilbert Space,RKHS)。其次基于最小P范数准则和正则化方法,推导得到自适应滤波器的最佳权向量,其降低了非高斯脉冲和样本量少的影响。然后利用矩阵求逆理论,推导得到矩阵的递归公式。最后利用核技巧得到在输入空间高效计算的滤波器输出和算法的迭代公式。α稳定分布噪声背景下Mackey-Glass时间序列预测的仿真结果表明:KRLMP算法与KRLS算法和KRMC算法相比,抗脉冲噪声能力强,鲁棒性好。展开更多
基金the Science Research Foundation of Qingdao Technological University(C2002-214)
文摘In this paper, we first give the concept of weakly P-inversive semigroup S（P）. Then we describe the strong P-congruences on S（P） in terms of their P-kernel normal systems. It is proved that there is a bijection between the strong P-congruences and the P-kernel normal systems. Finally, it is also prove that the lattice of strong P-congruences and the lattice of P-kernel normal systems on S（P） are isomorphic.
文摘Let S（P） be a P-inversive semigroup. In this paper we describe the strong P-congruences on S（P） in terms of their P-kernel normal systems. We prove that any strong P-congruence on S（P） can present a P-kernel normal system; conversely any P-kernel normal system of S（P） can determine a strong P-congruence.
文摘在强脉冲噪声干扰背景中,核递归最小二乘(Kernel Recursive Least Square,KRLS)算法和核递归最大相关熵(Kernel Recursive Maximum Correntropy,KRMC)算法对非线性信号预测性能严重退化,对此提出一种核递归最小平均P范数(Kernel Recursive Least Mean P-norm,KRLMP)算法。首先运用核方法将输入数据映射到再生核希尔伯特空间(Reproducing Kernnel Hilbert Space,RKHS)。其次基于最小P范数准则和正则化方法,推导得到自适应滤波器的最佳权向量,其降低了非高斯脉冲和样本量少的影响。然后利用矩阵求逆理论,推导得到矩阵的递归公式。最后利用核技巧得到在输入空间高效计算的滤波器输出和算法的迭代公式。α稳定分布噪声背景下Mackey-Glass时间序列预测的仿真结果表明:KRLMP算法与KRLS算法和KRMC算法相比,抗脉冲噪声能力强,鲁棒性好。
