Using Artificial Neural networks wireless to implement Machine Learning

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Hassan M. Ibrahim


In order to successfully deliver ubiquitous Internet connectivity, wireless networks can support the Internet of Things (IoT)use machine learning concepts integrated across the wireless core to allow intelligent, data-driven functions edge technology Machine learning techniques based on (ANNs) can resolving different wireless networking issues. To achieve this, we first give a thorough rundown of several important categories of recurrent, spiking, and deep neural network-based ANNs, uses of wireless networking that are relevant. For every kind of ANN, we present both the fundamental architecture and particular Examples for wireless networks that are very significant design. Long short-term memory, liquid state machines, and echo state networks are a few examples of this type. Then, we give a thorough review of the various wireless communication issues that can be solved with ANNs, covering anything from. We list future projects that can be addressed using ANNs, as well as the major reasons for employing them, for each unique application

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How to Cite
Hassan M. Ibrahim. (2022). Using Artificial Neural networks wireless to implement Machine Learning. Eurasian Journal of Engineering and Technology, 9, 13–18. Retrieved from