2012 IEEE International Conference on Circuits and Systems (ICCAS) 2012
DOI: 10.1109/iccircuitsandsystems.2012.6408280
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Artificial Neural Network model for microwave propagation in water melon

Abstract: The propagation and attenuation of microwave traversing through water melon at 2.45GHz were modeled and validated. An attenuation experiment was carried out on water melon using free space transmission technique and an Artificial Neural Network (ANN) was designed, trained and deployed for the observed data from laboratory experiments. This generated a compact system against which existing mathematical models were compared. The results in both cases were found to be in congruence.

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Cited by 2 publications
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“…As a result, the quest for the development of accurate, rapid and less Artificial Neural Networks (ANNs) in particular have been of great use in this regard, wherein their versatility, computational ease, speed and excellent capacity in solving non-linear problems have been exploited for the design of microwave devices. Efforts in this domain include the development of ANN based techniques for the characterization of organic tissues using microwave antennas [9,10]. Similar successful ANN-based works that are even more relatable to the domain of this paper include [11,12] where in the performances of cancer detecting microwave antennas were improved using the computing prowess of massively connected computing artificial nodes.…”
Section: Introductionmentioning
confidence: 95%
“…As a result, the quest for the development of accurate, rapid and less Artificial Neural Networks (ANNs) in particular have been of great use in this regard, wherein their versatility, computational ease, speed and excellent capacity in solving non-linear problems have been exploited for the design of microwave devices. Efforts in this domain include the development of ANN based techniques for the characterization of organic tissues using microwave antennas [9,10]. Similar successful ANN-based works that are even more relatable to the domain of this paper include [11,12] where in the performances of cancer detecting microwave antennas were improved using the computing prowess of massively connected computing artificial nodes.…”
Section: Introductionmentioning
confidence: 95%
“…Most of these soft computing techniques take their roots from the natural learning capabilities of living animals. Fuzzy inference system [6], for example, does this by adopting a logic that varies over a continuum from total inclusion to complete exclusion, as against the conventional crisp logic of only "0" and "1" [7]- [9]. Optimization problems have also enjoyed their share of the speed and ease of computing offered by soft computing-based optimization techniques like genetic algorithm (GA) and particle swarm optimization [10].…”
Section: Introductionmentioning
confidence: 99%