Hyperbolic Involutions and Quadratic Extensions

This is a variation on a theme of Bayer-Fluckiger, Shapiro, and Tignol related to hyperbolic involutions. More precisely, criteria for the hyperbolicity of involutions of quadratic extensions of simple algebras and involutions of the form σ ? τ and σ ? ρ, where σ is an involution of a central simple algebra A, τ is the nontrivial automorphism of a quadratic extension of the center of A, and ρ is an involution of a quaternion algebra are obtained.     

用正交投影迭代法求矩阵方程AXA~H=B的Hermite解

本文讨论了矩阵方程AXAH=B的Hermite解及其最佳逼近的正交投影迭代法,证明了算法的收敛性,得到收敛速率的估计式.通过数值试验也检验了算法的有效性.     

环F_p+uF_p+vF_p+uvF_p上的循环码

讨论了非有限链环R=F_p+uF_p+vF_p+uvF_p上的循环码.通过环R上的循环码与多项式环R_n=(F_p+uF_p+vF_p+uvF_p)[x]/(xⁿ-1)的理想的对应关系及对R_n的研究给出了R上循环码的刻画.最后定义了一个Gray映射,并刻画了F_p+uF_p+vF_p+uvF_p上的循环码在该映射下的像.     

Curvature identities derived from the integral formula for the first Pontrjagin number

We give an integral formula for the first Pontrjagin number of a compact almost Hermitian surface and derive curvature identities from the integral formula based on the fundamental fact that the first Pontrjagin number in the deRham cohomology group is a topological invariant. Further, we provide some applications of the identities.     

DLSTM-Based Successive Cancellation Flipping Decoder for Short Polar Codes

Polar code has been adopted as the control channel coding scheme for the fifth generation (5G), and the performance of short polar codes is receiving intensive attention. The successive cancellation flipping (SC flipping) algorithm suffers a significant performance loss in short block lengths. To address this issue, we propose a double long short-term memory (DLSTM) neural network to locate the first error bit. To enhance the prediction accuracy of the DLSTM network, all frozen bits are clipped in the output layer. Then, Gaussian approximation is applied to measure the channel reliability and rank the flipping set to choose the least reliable position for multi-bit flipping. To be robust under different codewords, padding and masking strategies aid the network architecture to be compatible with multiple block lengths. Numerical results indicate that the error-correction performance of the proposed algorithm is competitive with that of the CA-SCL algorithm. It has better performance than the machine learning-based multi-bit flipping SC (ML-MSCF) decoder and the dynamic SC flipping (DSCF) decoder for short polar codes.