提出了一种基于信息似然比的计算验前信息可信度的新方法。
A new method of calculating a prior information creditability is especially presented by using the concept of information likelihood rate.
该方法通过引入目标模型的鲁棒近邻信息以提高在环境不匹配情况下的似然比确认性能。
The method can improve the performance of likelihood ratio verification method in mismatch conditions by incorporating robust neighborhood information for a target model.
由于该算法充分利用了软译码得到的似然比信息，因此可以实现最优信号检测。
This algorithm can achieve the best demodulation because the likelihood ratio of information is used adequately.
对高维输入向量具有高的推广能力；比单源信息的SVM和最大似然方法图像分类精度更高，适合高空间分辨率遥感图像分类。
It has more accuration than the maximum likelihood method and SVM based on the single source data, adapts to the high spatial resolution RS Image classification.
多接收天线可以对判决似然比和迭代译码的外部信息提供分集增益，从而进一步提高系统性能。
Multi-receive antennas can also provide the diversity gain for LLR information and iterative extrinsic information.
多接收天线可以对判决似然比和迭代译码的外部信息提供分集增益，从而进一步提高系统性能。
Multi-receive antennas can also provide the diversity gain for LLR information and iterative extrinsic information.
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