ID	原文	译文
24405	联合约束滤波器的约束条件对第 1 级滤波器中的多模型集合中各子模型均有效。联合约束滤波器采用平滑约束卡尔曼滤波算法对第 1 级滤波结果进一步优化。	The latter is effective for everyone in model set of controlled plant and refines the estimation of the former using smoothly constraint Kalman algorithm.
24406	以机动目标实时跟踪为实际工程应用背景，数值仿真和飞行实验结果证明新的联合约束性级联交互式多模型滤波器比标准交互式多模型滤波器具有更小的估计误差和方差，所增计算量合理可行。	Numerical simulation and flying experiments are made for maneuvering target tracking and lower estimated error and covariance are achieved by the unified cascade constrained interactive multi-model Kalman filter compared with conventional interactive multi-model filter. The added computation cost is reasonable and acceptable.
24407	该文为交互式多模型滤波器和机动目标跟踪两个方向的进一步改进提供了有益借鉴。	The paper is a valuable reference for maneuvering target tracking and interactive multi-model filter.
24408	针对基于单一极化特性增强的极化SAR图像目标检测方法的缺陷，该文将DP(Dirichlet Process)混合隐变量SVM模型(DPLVSVM)应用于极化SAR图像舰船目标检测，提出一种基于多极化散射机理的检测方法。	Considering the shortcoming of detection method based on polarimetric contrast enhanced with single polarimetric scattering mechanism, a PolSAR detection method based on multiple polarimetric mechanisms called Dirichlet Process mixture of Latent Variable SVM (DPLVSVM) is proposed.
24409	该方法通过联合Dirichlet过程混合与Bayes SVM模型，将信号空间划分成若干局部区域，然后在每一局部区域学习一个独立的极化检测器，并将各局部检测器进行组合实现全局多极化散射机理的目标检测。	By assembling a set of local polarimetric detectors that based on single polarimetric scattering mechanism, a global multiple polarimetric scattering mechanisms detector is obtained.
24410	模型采用非参数化Bayes方法自动确定局部区域数量，在完全Bayes框架下，将局部区域划分及检测器学习进行联合优化，保证了各局部区域样本的可分性。	With a fully Bayes treatment, DPLVSVM learns the clustering and the local detectors jointly. Taking the advantage of Bayes nonparametric, DPLVSVM handles the model selection problem flexibly.
24411	另外，为了降低极化特征冗余，该文进一步提出带特征选择功能的稀疏提升DP混合隐变量SVM模型(SPDPLVSVM)，提高模型的推广能力。	Further, in order to reduce the redundancy of polarimetric feature and improve the model generalization, a model with feature selection, Sparsity-Promoting Dirichlet Process mixture of Latent Variable SVM (SPDPLVSVM), is proposed.
24412	该模型由于采用共轭先验分布，因而可以利用Gibbs采样方法进行高效求解。	Thanks to the conjugate property, the parameters in both of models can be inferred efficiently via the Gibbs sampler.
24413	在RADARSAT-2数据上进行的实验验证了所提方法的有效性。	Finally, the proposed models on RADARSAR-2 dataset is implemented to validate their effectiveness.
24414	基于失真函数的自适应隐写技术在嵌入过程中，忽略了嵌入操作相互间的影响，隐写策略无法随载体统计特性的改变自适应地调节。	Adaptive steganography ignores the interactive impact introduced by the embedding operation during the embedding operation.