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Parameters Estimation of Ultrasonics Echoes using the Cuckoo Search and Adaptive Cuckoo Search Algorithms

机译:使用杜鹃搜索和自适应杜鹃搜索算法的超声回波参数估计

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In this study we present a novel approach to estimate ultrasonic echo pattern using the two algorithms: Cuckoo Search (CS) and Adaptive Cuckoo Search (ACS). We model ultrasonic backscattered echoes in terms of superimposed Gaussian echoes corrupted by noise. Each Gaussian echo in the model is a non linear function of a set of parameters: echo bandwidth, arrival time, center frequency, amplitude and phase. The estimation of parameters is formulated as a nonlinear optimisation problem. Simulations are carried out to assess the performance of the proposed algorithms. Finally the algorithms were applied on experimental data for thickness measurement. The CS algorithm converges to best solution with less time than ACS. However, ACS algorithm outperforms CS.
机译:在这项研究中,我们提出了一种使用两种算法来估计超声回波模式的新颖方法:布谷鸟搜索(CS)和自适应布谷鸟搜索(ACS)。我们根据被噪声破坏的叠加高斯回波来建模超声反向散射回波。模型中的每个高斯回波都是一组参数的非线性函数:回波带宽,到达时间,中心频率,幅度和相位。参数的估计被公式化为非线性优化问题。进行仿真以评估所提出算法的性能。最后,将算法应用于实验数据进行厚度测量。与ACS相比,CS算法可以以更少的时间收敛到最佳解决方案。但是,ACS算法的性能优于CS。

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