One of the most powerful and versatile system identification frameworks of the last three decades is the NARMAX/NARX approach, which is based on a nonlinear discrete-time representation. Recent advances in machine learning have motivated new functional forms for the NARX model, including one based on Gaussian processes (GPs), which is the focus of this paper. Because of their nonparametric form...

Abstract Aiming to improve the position and velocity precision of INS/GNSS system during GNSS outages, a novel that combines unscented Kalman filter (UKF) nonlinear autoregressive neural networks with external inputs (NARX) is proposed. The NARX-based module utilized predict measurement updates UKF outages. A new offline approach for selecting optimal NARX suggested tested. This based ...

Complex dynamic behavior of nonlinear structures makes it challenging for uncertainty analysis through Monte Carlo simulations (MCS). Surrogate modeling presents an efficient and accurate computational alternative a large number MCS. The previous study has demonstrated that the multi-input multi-output autoregressive with exogenous input (MIMO-NARX) model provides good discrete-time representat...

Gaussian processes (GP) regression is a powerful probabilistic tool for modeling nonlinear dynamical systems. The downside of the method its cubic computational complexity with respect to training data that can be partially reduced using pseudo-inputs. dynamics represented an autoregressive model, which simplifies static case. When simulating uncertainty propagated through function and simulati...

Due to the advances of network technologies and multimedia communications, Quality of Service (QoS) becomes an increasingly important issue in network communications. Many traditional assessment techniques were designed to evaluate the QoS of multimedia applications transmitted over these networks. In this paper, a new QoS evaluation system has been developed. The proposed system is based on us...

The HAMP linker, a predicted structural element observed in sensor proteins from all domains of life, is proposed to transmit signals between extracellular sensory input domains and cytoplasmic output domains. HAMP (histidine kinase, adenylyl cyclase, methyl-accepting chemotaxis protein, and phosphatase) linkers are located just inside the cytoplasmic membrane and are projected to form two shor...

Introduction In order to improve the quality of life of amputees, biomechatronic researchers and biomedical engineers have been trying to use a combination of various techniques to provide suitable rehabilitation systems. Diverse biomedical signals, acquired from a specialized organ or cell system, e.g., the nervous system, are the driving force for the whole system. Electromyography(EMG), as a...

The complex interactions between vapour-liquid equilibrium, mass and energy transports and reaction kinetics in reactive distillation (RD) process have constituted serious computational challenges to its modelling and control. This is because large numbers of nonlinear differential algebraic equations are needed to represent the process when using first principle modelling approach. This work d...

Mycobacterium tuberculosis is one of the strongest reducers of nitrate in the genus Mycobacterium: Under microaerobic conditions, whole cells exhibit upregulation of activity, producing approximately eightfold more nitrite than those of aerobic cultures of the same age. Assays of cell extracts from aerobic cultures and hypoxic cultures yielded comparable nitrate reductase activities. Mycobacter...

Tide variations are affected not only by periodic movement of celestial bodies but also time-varying interference from the external environment. To improve accuracy tide prediction, a modular level prediction model (HA-NARX) is proposed. This divides data into two parts: astronomical tide-generating forces and nonastronomical various environmental factors. Final results obtained using nonlinear...