信息损失 meaning in Chinese
information loss
loss of information
Examples
- Due to the difference degree of information lost in haze and dense fog , different methods are adopted
由于轻雾天气和大雾天气下图像信息损失程度的不同，对它们分别采用不同的手段进行处理。 - At the same time , i discover the relations between the m . west method and gonden et al method in the discussing of the information losing
并且在讨论抽样过程中模型参数的信息损失问题时，发现了m . west和gondenetal方法之间内在的联系。 - After analyzing and study two transitions of map to spatial data and spatial data to map , the author thinks the spatial data capturing is a loss map information process , and for map production firstly symbolize from spatial data , then reinforce the map information . the map production model ( mpm ) is the summary of all kinds of map production . the integration model is the best model in mpm and it infers that " spatial data first , map second " is the production process
提出了“静态数字制图”和“动态数字制图”的概念，论述它们各自特点和研究方法，并提出地图制图和空间数据生产都属于“静态数字制图” ；通过研究地图和空间数据的相互转换过程，发现空间数据生产是地图信息损失的过程，根据空间数据来进行地图生产必须先实现地图符号化，然后再进行地图信息的补充处理；本文提出的“地图生产模型”是现有各种数字化生产模式的基础，从理论上论证了一体化生产模式是最优模式，推导出“先空间数据生产，后地图出版”的一体化生产流程，并归纳总结了当前数字化生产的4种基本生产模式和9种应用情况。 - Second , based on the theory of synthetic discriminant function , several sub - reference images were synthesized to form the reference image base to realize rotation distortion - invariant recognition , which also solved the ill - problem of synthesizing a single reference image with the whole training distorted images and made the pose estimation easier . third , the phase - encoding and amplitude modulation distortion - invariant jtc for multi - target recognition were described
其次，论文采用综合识别函数方法构成子参考图像，建立参考图像库的方法解决了目标旋转畸变不变的识别问题，克服了由大量训练图像合成单幅参考图像时，高频信息损失严重的病态问题，并可实现对真实目标旋转姿态的估计。 - 2 ) by analyzing the information and conditional information description mechanism of system states , the problem of stochastic model reduction is investigated based on state aggregation . the information loss and conditional information loss between the full - and reduced - order models are measured by entropy , while the independence and conditional independence within me components of aggregated state are measured by kullback - leibler information distance . several model reduction methods for stable and unstable linear systems are derived by employing two criteria to get aggregation matrices : the minimal information loss and the maximal independence
2 )分析了随机系统状态空间模型中的信息和条件信息描述机制，以shannon熵为手段描述线性系统模型降阶过程中的信息和条件信息损失，以kullback - leibler信息作为衡量降阶模型状态向量各分量之间统计独立性的测度，针对稳定和不稳定系统研究基于状态集聚的模型降阶问题：分别运用最小信息损失准则和最大独立性原则，得出几种状态集聚的信息论方法，并讨论降阶模型的性质、阶次的确定、系统噪声分布特性等问题。