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 Article10.9734/ajrcos/2021/v9i430228
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 Article10.9734/ajrcos/2020/v6i430163
The Residue Number System (RNS) is a non-positional number system that represent number in the form of residues modulo a set of coprime moduli. This nature of RNS makes it advantageous in achieving carry-free arithmetic. However, due to the non-positional nature of RNS, direct nu...
Open access
Research Article10.9734/ajrcos/2026/v19i3841
The Residue Number System (RNS) offers significant advantages in parallel, carry-free arithmetic for highperformance computing but remains critically vulnerable to errors during transmission and computation. Traditional error detection approaches rely on post-processing reverse c...
Open access
Research Article10.9734/ajrcos/2026/v19i1802