target data model

2-D track-to-measurement association approach, a BP based Variable Structrue Interaction Multiple Model ( IMM), is proposed to simultaneously resolve the two most important uncertainties existed in the data association problem, i.e. measurement origin uncertainty and target motion uncertainty.

为了同时解决存在于航迹与量测互联问题中的两种不确定性：目标运动和量测源的不确定性，本文提出一种基于BP的变结构交互式多模型2D互联技术。

Intelligent client was adopted. The radar RCS analysis and calculate model and the infrared target characteristic abstract model were integrated which made the target characteristic data were stored in the database automatically. 2.

主要特点是：1.采用智能客户端的形式，集成了雷达RCS分析计算模型和红外目标提取模型，实现了目标特征数据的自动入库功能。

The paper recalled GIS data model evolution on the basis of a representative model to study the dynamics of space-based target data model acts, and as an example to emergency vehicles designed for monitoring the realization of the model structure.

本文在回顾GIS数据模型演变过程中几个代表性模型的基础上，研究了基于空间对象动态行为的数据模型。

Iterative target transformation factor analysis was applied to resolve the kinetic-spectral data matrix monitored in the process of spectroscopic reaction of unknown kinetic model and the kinetic spectrum of each component is obtained.

采用迭代目标转换因子分析法（ITTFA）解析动力学模型未知的化学反应过程中的动力学-光谱数据矩阵，获得了各组分的动力学谱。

It is further assumed that the target data model is defined.

并进一步假设已经定义了目标数据模型。

The target model is used to search class characters based on analysis of training data.

目标模型是通过对训练样本数据的分析找到反映各类别的特征。

Target Bearing Data Pre-Processing based on GM ( 1,1) Grey System Model

GM（1,1）模型用于目标方位数据预处理

The data consolidation pattern does not require a specific target data model.

数据整合模式并不需要特定的目标数据模型。

If an operational data store ( ODS) or a master data management ( MDM) system is to be created to support the SOA solution, then the target is the physical data model for this data store.

如果要创建一个操作数据存储（operational data store，ODS）或主数据管理（MDM）系统来支持SOA解决方案，那么目标是这个数据存储的物理数据模型。

Gaussian mixture model ( Gaussian Mixture Models, GMM) is an important method of machine learning, which aims to establish a probability model for the target data set.

高斯混合模型（Gaussian mixture models，GMM）是一种重要的机器学习方法，其目的是建立目标数据集的概率模型。