ID 原文 译文
22385 仿真结果表明，所提算法可以提高各优化目标的求解精度，从而提高业务接入成功率和网络资源利用率，并且为决策者提供多种接入方案，可根据实际需求进行最优选择。 The  simulation  results  show  that  the  proposed  algorithm  improves  the  accuracy  of  each optimization objective, and thus improves the success rate of access and the utilization ratio of network resources. It can also provide a variety of optimal access control schemes for decision makers, which can be optimally chosen according to actual requirements.
22386 针对高误码率情况下(n,1,m)卷积码的盲识别问题，该文提出一种新的基于改进 Walsh-Hadamard 变换(Walsh-Hadamard Transform, WHT)的方法。 Considering the blind recognition of (n,1,m) convolutional codes at high bit error rate, a novel method based on modified Walsh-Hadamard Transform (WHT) is presented.
22387 首先将原问题等效为多路 1/2 码率卷积码的盲识别问题，并建立关于其生成多项式系数的线性方程组。 First, the original issue is equivalent to the blind recognition of several 1/2 rate convolutional codes, and a system of linear equations for generating polynomial coefficients is established.
22388 然后分析了现有基于 WHT 的方法直接求解该方程组所存在的不足，重新建立更稳健的判决门限，同时通过缩小解的取值范围降低计算量，进而在求得正确解向量的同时完成对码长的识别。 Disadvantages of the existing methods based on WHT are analyzed, after which a more robust decision threshold is deduced, with a reduction in computational complexity by limiting the range of roots, and then the code length is recognized while the correct solution vector is found.
22389 最后，将多路等效 1/2 码率卷积码的生成多项式按一定条件组合，得到(n,1,m)卷积码的生成多项式矩阵。 Finally, the generator polynomial matrix of (n,1,m) convolutional codes is obtained by combining the generator polynomial of the equivalent 1/2 rate convolutional codes.
22390 仿真结果验证了所提方法的有效性，且性能优于传统方法。 The simulation results verify the effectiveness of the proposed method, which has a better performance when comparing to the traditional method.
22391 针对传统点集非刚体配准算法对复杂局部形变数据配准精度低，收敛速度慢等问题，该文提出一种基于局部仿射配准的鲁棒非刚体配准算法。 To solve the problem that the traditional point set non-rigid registration algorithm has low precision and slow convergence speed for complex local deformation data, this paper proposes a robust non-rigid registration algorithm based on local affine registration.
22392 该算法采用分层迭代的方式由粗到精地完成点集的非刚体配准。 The algorithm uses a hierarchical iterative method to complete the non-rigid registration of the point set from coarse to fine.
22393 在每层迭代中，首先对子形状点集集合和子目标点集集合进行分块处理并更新分块后每一类子点集的形状控制点。 In each iteration, the sub shape point sets and sub target point sets are divided and the shape control points of each sub point set are updated.
22394 然后利用控制点引导仿射迭代最近点(ICP)算法求解对应子点集间的局部仿射变换。 Then the control point guided affine Iterative Closest Point (ICP) algorithm is used to solve the local affine transformation between the corresponding sub point sets.