| 基于序列大数据增量式挖掘算法的多模态通信信号同步方法 |
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| 引用本文：杜婧子.基于序列大数据增量式挖掘算法的多模态通信信号同步方法[J].计算技术与自动化,2025,(3):1-5 |
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| 中文摘要:在多模态通信信号同步中，由于信号特征较为复杂，对后续的频偏估计过程造成了一定的干扰，导致信号同步处理结果的TIE值比较高。为此，提出了基于序列大数据增量式挖掘算法的多模态通信信号同步方法。通过建立多模态通信信号的信道模型，采用序列大数据增量式挖掘算法对信号进行聚类处理，由此提取出不同聚类簇的信号时序特征。结合该特征，对信号执行M次方运算，从而利用FFT变换的方法估计相应的信号频偏。在此基础上，通过并行捕获的方法对信号频偏进行修正，从而实现多模态通信信号的同步处理。经过实验测试可知，该方法在时间间隔误差（Time Interval Error,TIE）指标方面表现出了较低的数值水平，信号的同步效果更优，在多模态通信领域中有着良好的应用前景。 |
| 中文关键词:信号同步 多模态通信信号 增量式挖掘算法 序列大数据 通信信号 信号处理 |
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| Multi Modal Communication Signal Synchronization Method Based on Incremental Mining Algorithm of Sequence Big Data |
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| Abstract:In multimodal communication signal synchronization, due to the multiple modes of the signal, the characteristics of the signal are more complex, which causes certain interference to the subsequent frequency offset estimation process, resulting in a relatively high TIE value of the signal synchronization processing result. To alleviate this problem, a multimodal communication signal synchronization method based on incremental mining algorithm of sequence big data is proposed. By establishing a channel model for multimodal communication signals and using sequential big data incremental mining algorithms to cluster the signals, the signal temporal characteristics of different clustering clusters are extracted. Based on this feature, perform M operations on the signal to estimate the corresponding signal frequency offset using FFT transform method. On this basis, the signal frequency offset is corrected through parallel capture method to achieve synchronous processing of multimodal communication signals. Through experimental testing, it has been found that this method exhibits a relatively low numerical level in terms of TIE index, with better signal synchronization effect, and has good application prospects in the field of multimodal communication. |
| keywords:signal synchronization multimodal communication signals incremental mining algorithm sequential big data communication signals signal processing |
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