This paper investigates the use of non-linear autoregressive exogenous (NARX) artificial neural networks (ANNs) to achieve black-box average dynamic models dc-dc converters capable capturing main converter non-linearities. Non-linearities may include, for example, behavior variations due changes operating point or mode (e.g., discontinuous conduction mode, continuous mode). presents design guid...

We study the complexity of some computational problems on finite black-box rings whose elements are encoded as strings of a given length and the ring operations are performed by a black-box oracle. We give a polynomial-time quantum algorithm to compute a basis representation for a given black-box ring. Using this result we obtain polynomial-time quantum algorithms for several natural computatio...

Efficient and thorough testing is essential to create quality software. In some cases, software code may not be available in testing phase. In such scenarios black box testing is used. The work presents various black box testing techniques. A systematic literature review has been carried out according to the guidelines proposed by kitchenham. The work discusses the applicability of artificial i...

Variational inference has become a widely used method to approximate posteriors in complex latent variables models. However, deriving a variational inference algorithm generally requires significant model-specific analysis. These efforts can hinder and deter us from quickly developing and exploring a variety of models for a problem at hand. In this paper, we present a “black box” variational in...