Traditionally, blind channel identification and equalization are all based on high order statistics.
传统的盲信道辨识和均衡都是基于高阶统计算法。
Based on maximum kurtosis criteria, a new blind identification and equalization algorithm is designed for linear system.
根据最大峰度准则设计了一种针对线性系统的盲辨识与盲均衡算法。
In this paper, the problem of blind identification and blind equalization of digital communication systems based on the second-order statistics (SOS) are addressed.
本文主要介绍了基于二阶统计量(SOS)的数字通信系统的盲辨识和盲均衡。
Blind identification and equalization has been received considerable attention recently in communication and signal processing, the main work of this dissertation is on this topic.
近年来，盲信道辨识与均衡在通信和信号处理领域已经受到普遍关注。
Traditionally, blind channel identification and equalization are all based on high order statistics, which are known to suffer from many drawbacks.
传统的盲信道辨识和均衡都是基于高阶统计算法，从而存在许多弊端。
Blind equalization and blind channel identification mean that estimate the unknown sending signals and unknown channel respectively when there is no training serials.
“盲均衡”和“盲辨识”分别是指在不需要训练序列的条件下，对未知发送信号的估计和对未知信道的估计。
Blind equalization and blind channel identification mean that estimate the unknown sending signals and unknown channel respectively when there is no training serials.
“盲均衡”和“盲辨识”分别是指在不需要训练序列的条件下，对未知发送信号的估计和对未知信道的估计。
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