Baagyere, Edward Yellakuor

Spiking Neural Network Learning Models for Spike Sequence Learning and Data Classification

Moses Apambila Agebure, Baagyere, Edward Yellakuor, Agebure, Moses Apambila, Edward Yellakuor Baagyere, Oyetunji, Elkanah Olaosebikan & Elkanah Olaosebikan Oyetunji · Asian Journal of Research in Computer Science · 2020

Supervised learning in Spiking Neural Network (SNN) is a hotbed for researchers due to the advantages temporal coded networks provide over that of rate-coded networks with respect to efficiency in information processing and transfer rates. Supervised learning in rate-coded networ...

Open access Research Article 10.9734/ajrcos/2020/v6i430163

Efficient Elliptic Curve Arithmetic for Lightweight Cryptographic Schemes for IoT Applications

Iddrisu, Mohammed Muniru, Zakaria Abukari, Baagyere, Edward Yellakuor, Edward Yellakuor Baagyere, Mohammed Muniru Iddrisu & Abukari, Zakaria · Asian Journal of Research in Computer Science · 2022

The Internet of Things’ (IoT) market is expected to grow exponentially at the global level in the coming years, due to the proliferation of more reliable and faster networks resulting from the extensive rollout of 5 to 10 G mobile networks. By 2025, it is expected that worldwide...

Open access Research Article 10.9734/ajrcos/2022/v14i4307

A Survey of Supervised Learning Models for Spiking Neural Network

Moses Apambila Agebure, Wumnaya, Paula Aninyie, Baagyere, Edward Yellakuor, Paula Aninyie Wumnaya, Edward Yellakuor Baagyere & Agebure, Moses Apambila · Asian Journal of Research in Computer Science · 2021

There has been a significant attempt to derive supervised learning models for training Spiking Neural Networks (SNN), which is the third and most recent generation of Artificial Neural Network (ANN). Supervised SNN learning models are considered more biologically plausible and th...

Open access Research Article 10.9734/ajrcos/2021/v9i430228