ID 原文 译文
19495 针对复杂环境下，单测量矢量(SMV)条件下的正交频分复用(OFDM)时延估计问题，该文提出了一种基于贝叶斯自动相关性确定(BARD)的稀疏重构时延估计算法。 Considering the problem of Orthogonal Frequency Division Multiplexing (OFDM) signal delayestimation with only a Single Measurement Vector (SMV) in a complex environment, a sparse reconstructiontime delay estimation algorithm based on Bayesian Automatic Relevance Determination (BARD) is proposed.
19496 该算法运用贝叶斯框架，从进一步挖掘有用信息的角度入手，引入不对称的自动相关性确定(ARD)先验，融入参数估计过程中，有效提升了低信噪比(SNR)和SMV条件下的时延估计精度。 The Bayesian framework is used to start from the perspective of further mining useful information, andasymmetric Automatic Relevance Determination(ARD) priori is introduced to integrate into the parameterestimation process, which improves the accuracy of time delay estimation under SMV and low Signal-to-NoiseRatio (SNR) conditions.
19497 该算法首先基于OFDM信号物理层协议数据单元估计出的信道频域响应构造稀疏化实数域表示模型，然后对模型中的噪声和稀疏系数矢量进行概率假设，同时引入自动相关性确定先验； Firstly, a sparse real-domain representation model is constructed based on theestimated frequency domain response of the OFDM signal physical layer protocol data unit. Then, probabilityhypothesis for the noise and sparse coefficient vectors are made in the model, and Automatic RelevanceDetermination (ARD) prior is introduced.
19498 最后根据贝叶斯框架，通过期望最大化(EM)算法求解超参数，实现对时延的估计。 Finally, according to the Bayesian framework, the Expectation Maximization (EM) algorithm is used to solve the hyper parameters to estimate the delay.
19499 仿真实验表明，该算法具有更好的估计性能，在信噪比较高时更加贴近克拉美罗界(CRB)。 The simulationexperiments show that the proposed algorithm has better estimation performance and is closer to theCramér–Rao Bound (CRB).
19500 同时基于通用软件无线电外设(USRP)，利用实际信号对所提算法进行了有效性地验证。 At the same time, based on the Universal Software Radio Peripheral (USRP), the effectiveness of the proposed algorithm is verified by the actual signal.
19501 针对现有的人机交互系统普遍存在情感缺失、参与人参与度不高的问题，该文依据PAD情感空间提出一种基于博弈的机器人认知情感交互模型。 To solve the problems of the existing in the process of human-computer interaction system, such a slack of emotion and low participation, a cognitive emotion interaction model based on game theory in PAD emotion space is proposed.
19502 首先，对参与人的交互输入情感进行评估并分析当前人机交互关系，提取友好度和共鸣度2个影响因素。 Firstly, the interactive input emotion of participant is evaluated and some influencefactors such as friendship and resonance are extracted to analyze the current human-computer interactionrelationship.
19503 其次，模拟人际交往的心理博弈过程对参与人和机器人的情感生成过程进行建模，将嵌入博弈的子博弈完美均衡策略作为机器人的最优情感选择策略； Secondly, modeling the emotional generation process of participants and robots by simulating the psychological game process in interpersonal communication, and the optimal emotional strategy of the robot is obtained by using the sub-game perfection equilibrium of the embedded game.
19504 最后，根据最优情感策略更新机器人的情感状态转移概率，并以6种基本情感的空间坐标为标签，得出受到情感刺激后机器人情感状态的空间坐标。 Finally, the emotional state transition probability of the robot is updated according the optimal emotional strategy. The spatial coordinates of the six basic emotional states are used as labels to obtain the PAD spatial coordinate of the robot emotional state after emotional stimulate.