Abstract
In order to evaluate the material charateristics and defects, different input signals are allowed to pass through the material. These signals are able to capture the hidden information regarding the material while traversing througnh it. These material signatures can be obtained by analyzing the reflected signals. This enables us to study the material properties and defects non-invasively. The different input signals can be modelled as Chirp signal, Gaussian echo, combination of echoes, etc. In this paper, analysis is done using chirp as the input signal. The parameter estimation is done using Maximum Likelihood and different optimization techniques are adopted for minimizing the error. Eventhough the results obtained for all optimization algorithms are comparable with the actual parameters, Levenberg-Marquardt algorithm gave the best fit, with minimum average absolute relative error.
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Anuraj, K., Poorna, S.S. (2020). Performance Analysis of Optimization Algorithms Using Chirp Signal. In: Smys, S., Bestak, R., Rocha, Á. (eds) Inventive Computation Technologies. ICICIT 2019. Lecture Notes in Networks and Systems, vol 98. Springer, Cham. https://doi.org/10.1007/978-3-030-33846-6_15
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DOI: https://doi.org/10.1007/978-3-030-33846-6_15
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