Abstract: Revealing the latent low-dimensional geometric structure of high-dimensional data is a crucial task in unsupervised representation learning. Traditional manifold learning, as a typical ...

Understanding the preferences of potential users of digital health products is beneficial for digital health policy and planning. Stated preference methods could help elicit individuals’ preferences ...

Abstract: In a practical alternating current (ac) machine drive system, a zero-order hold equivalent discrete-time machine model motivates the development of a direct discrete-time current regulator ...