This study was conducted to determine if artificial neural networks (ANN) can be used to
accurately predict in vitro organogenesis of Bacopa monnieri compared with statistical …

A novel fully connected recurrent neural network (FCRNN) structure is proposed for the
identification of unknown dynamics of nonlinear systems. The proposed recurrent structure …

Introduction Tracking the hidden states of dynamic systems is a fundamental task in signal
processing. Recursive Kalman Filters (KF) are widely regarded as an efficient solution for …

Under the influence of multiple types of noises, missing measurement, one-step
measurement delay and packet loss, the robust Kalman estimation problem is studied for the …

The training algorithm is a determining factor in the success of artificial neural networks.
Until now, first-order optimizers based on gradient descent are the most used in neural …

The Evidence Lower Bound (ELBO) is a widely used objective for training deep generative
models, such as Variational Autoencoders (VAEs). In the neuroscience literature, an …

A process that is almost always present in the chemical industry is distillation. The plant
used in this study is a batch-type distillation column system located in the ITB Honeywell …

Online monitoring of mechatronic systems and production environments helps operators to
steer their processes into regions of optimal performance. Filtering methods, such as the …

Ca urmare a noii revoluții industriale (Industry 4.0), ne regăsim într-o perioadă caracterizată
de automatizarea, digitizarea și interconectarea componentelor din procesele de producție …

MAINTENANCE PLATFORM IN INDUSTRY 4.0 - Abstract - Page 1 Industry 4.0
Maintenance Platform 1 UNIVERSITY POLITEHNICA OF BUCHAREST FACULTY OF …