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• W4313215789 abstract "Intelligent signal processing offers a variety of methods for communication system design and operation, including fuzzy logic, neural networks and evolutionary computation. This study proposes a novel technique for designing a mobile sensor network algorithm based on wireless security to provide a secure as well as energy-efficient communication system that allows sensor swarms to move while maintaining optimal sensor node spacing. Here signal feature extraction has been done using cuckoo Meta search algorithm (Cu_MeSA) and classification using Fuzzy based Boltzmann convolution machine neural network with (Fuz_Bol_ConVMNN) architecture. The experimental results shows that the output signal of feature extraction and classification with comparative parametric analysis in terms of packet arrival rate, network lifespan, energy optimization, probability of attack detection, throughput." @default.
• W4313215789 created "2023-01-06" @default.
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• W4313215789 date "2023-02-01" @default.
• W4313215789 modified "2023-09-26" @default.
• W4313215789 title "Collaborative autonomous system based wireless security in signal processing using deep learning techniques" @default.
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• W4313215789 doi "https://doi.org/10.1016/j.ijleo.2022.170313" @default.
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