Edge computing is a paradigm in which data intelligently processed close to its source. Along with advancements deep learning, there growing interest using neural networks at the edge for predictive analytics. Given realistic constraints computational resources of devices, this combination challenging. In order bridge gap between learning models and efficient analytics, container-based framewor...

in many active noise control (anc) applications, an online secondary pathmodelling method that uses a white noise as a training signal is required. this paperproposes a new feedback anc system. here we modified both the fxlms and thevss-lms algorithms to raised noise attenuation and modelling accuracy for theoverall system. the proposed algorithm stops injection of the white noise at theoptimum...

Abstract Advances in artificial neural networks (ANN), specifically deep learning (DL), have widened the application domain of process control. DL algorithms and models become quite common these days. The training algorithm is most important part an ANN that affects performance controller. Training optimize weights biases according to input-output patterns. In this paper, different was evaluate...