Abstract
In this work, FLANN structure is presented which can be utilized to construct nonlinear channel equalizer. This network has a modest structure in which nonlinearity is instigated by the functional expansion of input pattern by trigonometric and Chebyshev polynomials. This work also defines evolutionary approaches coined as firefly algorithm (FFA) along with modified variable step size firefly algorithm for resolving channel equalization complixeties using artificial neural network. This paper recapitulates techniques with simulated results acquired for given channel with certain noise conditions and justify the efficacy of proposed FLANN-based channel equalizer using VSFFA over FFA and PSO in terms of MSE curves and BER plots.
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Sarangi, A., Sarangi, S.K., Mukherjee, M., Panigrahi, S.P. (2018). Functional Link Artificial Neural Network-Based Equalizer Trained by Variable Step Size Firefly Algorithm for Channel Equalization. In: Bhateja, V., Tavares, J., Rani, B., Prasad, V., Raju, K. (eds) Proceedings of the Second International Conference on Computational Intelligence and Informatics . Advances in Intelligent Systems and Computing, vol 712. Springer, Singapore. https://doi.org/10.1007/978-981-10-8228-3_44
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DOI: https://doi.org/10.1007/978-981-10-8228-3_44
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