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Adaptive filtering noisy transcranial Doppler signal by using artificial bee colony algorithm

机译:人工蜂群算法自适应滤波经颅多普勒信号

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Computerized processes are supportive in the new age of medical treatment. Biomedical signals which are collected from the human body supply or important useful data that are related with the biological actions of human body organs. However, these signals may also contain some noise. Heart waves are commonly classified as biomedical signals and are non-stationary due to their statistical specifications. The probability distributions of the noise are very different, and for this reason there is no common method to remove the noise. In this study, adaptive filters are used for noise elimination and the transcranial Doppler signal is analyzed. The artificial bee colony algorithm was employed to design the adaptive IIR filters for noise elimination on the transcranial Doppler signal and the results were compared to those obtained by the methods based on popular and recently introduced evolutionary algorithms and conventional methods.
机译:在新的医学治疗时代,计算机化过程是有帮助的。从人体收集的生物医学信号或与人体器官的生物学行为有关的重要有用数据。但是,这些信号也可能包含一些噪声。心电波通常被归类为生物医学信号,并且由于其统计指标而不稳定。噪音的概率分布非常不同,因此,没有通用的消除噪音的方法。在这项研究中,自适应滤波器用于消除噪声,并分析经颅多普勒信号。采用人工蜂群算法设计了自适应IIR滤波器,以消除经颅多普勒信号的噪声,并将结果与​​基于流行和最近引入的进化算法和常规方法的方法所获得的结果进行了比较。

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