@InProceedings{8553222,
  author = {F. Chibane and A. Benammar and R. Drai},
  booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
  title = {Parameters Estimation of Ultrasonics Echoes using the Cuckoo Search and Adaptive Cuckoo Search Algorithms},
  year = {2018},
  pages = {2415-2418},
  abstract = {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.},
  keywords = {acoustic noise;backscatter;echo;Gaussian noise;optimisation;parameter estimation;search problems;thickness measurement;ultrasonic materials testing;ultrasonic scattering;ultrasonic echo pattern;superimposed Gaussian echoes;nonlinear function;CS algorithm;ACS algorithm;Adaptive Cuckoo Search algorithms;ultrasonic backscattered echoes;parameter estimation;noise;echo bandwidth;arrival time;nonlinear optimisation problem;thickness measurement;Signal processing algorithms;Acoustics;Delamination;Parameter estimation;Birds;Optimization;cuckoo search algorithm;echo parameter estimation;ultrasonic signal;thikness measurement},
  doi = {10.23919/EUSIPCO.2018.8553222},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570439314.pdf},
}

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Drai},\n booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},\n title = {Parameters Estimation of Ultrasonics Echoes using the Cuckoo Search and Adaptive Cuckoo Search Algorithms},\n year = {2018},\n pages = {2415-2418},\n abstract = {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. 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