ID 原文 译文
23745 光无线融合网络中光域和无线域存在速率不匹配以及业务分类不同的问题。 There are mismatches of transmission rates and different service classifications between optical domain and wireless domain in Wireless-Optical Broadband Access Network (WOBAN).
23746 为提高融合网络的 QoS 及充分利用网络资源，该文提出一种基于令牌桶算法的流量整形策略。 To improve the QoS of the integration network and make full use of network resources, a new algorithm based on token bucket traffic shaping policy is proposed.
23747 根据 EPON 与 WiMAX 业务的 QoS 映射以及调度策略，以业务在整个网络中的相对优先级来决定令牌桶参数的选择，并结合更符合实际的自相似网络流量推导出最佳令牌桶参数计算公式，并在此基础上，提出基于优先级的共享缓存策略，进而，得到通过 QoS 指标的变化而自适应动态调整的流量整形策略。仿真结果表明，所提流量整形策略能够有效降低网络设备压力，同时提高整个融合网络的 QoS。 According to the service mapping rules and scheduling of EPON and WiMAX, the selection of token bucket parameters B determined based on the relative service priority of the entire network. This paper also combines with more realistic self-similar network traffic to derive the best formula for token bucket parameters and then proposes a shared buffer strategy on the basis of the service priority. Furthermore, an adaptively dynamically adjust traffic shaping policy is obtained through the change of QoS metrics. The simulation results show that the proposed strategy can effectively reduce traffic shaping network equipment pressure while improving the QoS of whole converged networks.
23748 针对超短基线水声定位系统面临的相位差模糊问题，该文提出一种基于多分类器融合的定位解模糊算法。 To solve the phase-difference ambiguity problem in Ultra-Short BaseLine (USBL) underwater acoustic positioning systems, an ambiguity resolution and localization method based on Multiple Classifier Fusion (MCF) is proposed.
23749 首先构建多分类器系统，将解模糊问题转化为对模糊数进行分类识别的问题，并采用 Choquet 积分对各分类器结果进行融合，得到模糊数所属类别，进而对目标进行定位。 Firstly, the multiple classifier system is built. Then, ambiguity resolution problem is formulated as classifying and recognizing the ambiguity integer, and Choquet integral is utilized for fusing the results of multiple classifiers. Finally, the category of ambiguity integer is obtained and the target is located.
23750 给出了目标位置的无模糊观测条件。 The unambiguous observation condition of the target position is derived.
23751 该算法优点是无需构造小于半波长间距的阵列，有效扩大了无模糊阵列孔径，而且由于充分利用了相位差观测数据的统计特性，定位精度可接近克拉美-罗界。 Without constructing an inter-sensor spacing less than half the wavelength, unambiguous aperture of the array is effectively enlarged. Moreover, as statistical characteristics of the observation data are fully utilized, the positioning accuracy approaches the Cramer-Rao bound.
23752 仿真结果验证了该算法的有效性。 Simulation results verify the effectiveness of the proposed method.
23753 为提高低信噪比条件下宽带欠定信号 DOA 估计精度，该文提出基于网格失配迭代最小化稀疏学习的宽带DOA 估计方法。 In order to improve underdetermined wideband signals DOA estimation accuracy under low Signal to Noise Ratio (SNR) condition, an off-grid sparse learning via iterative minimization algorithm is proposed.
23754 该方法首先对频域协方差矩阵进行矢量化处理实现虚拟阵列扩展，将欠定信号转换为超定信号。 Firstly, the novel algorithm vectorizes the covariance matrix in frequency domain to realize visual array extension, as a result, underdetermined wideband signals are transformed into overdetermined signals.