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Neuro-Fuzzy Model for the Prediction of Spectral Occupancy

机译:用于预测光谱占用的神经模糊模型

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摘要

Modeling spectral occupancy in cognitive radio networks facilitate the prediction of the primary user's activity and contribute to an efficient use of the radio-electric spectrum. The purpose of this article is to develop a neuro-fuzzy model to predict the spectral occupancy in a Wi-Fi network (2.4 to 2.5 GHz). To achieve this, the ANFIS algorithm is implemented and its performance is evaluated for two types of membership functions, through the comparison of their results. The obtained results validate the performance of the neuro-diffuse model and its usefulness within cognitive wireless networks.
机译:认知无线电网络中的建模光谱占用促进了对主要用户的活动的预测,并有助于有效地使用无线电谱。 本文的目的是开发一个神经模糊模型,以预测Wi-Fi网络(2.4到2.5 GHz)中的光谱占用。 为此,通过对其结果的比较来实现ANFIS算法,并评估其两种类型的隶属函数的性能。 所获得的结果验证了神经漫射模型的性能及其在认知无线网络中的用途。

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