The present study investigates the prediction efficiency of nonlinear system-identification models, in assessing the behavior of a coupled structure-passive vibration controller. Two system-identification models, including Nonlinear AutoRegresive with eXogenous inputs (NARX) and adaptive neuro-fuzzy inference system (ANFIS), are used to model the behavior of an experimentally scaled three-story...

Bill G. Horne NEC Research Institute 4 Independence Way Princeton, NJ 08540 c. Lee Gilest NEC Research Institute 4 Independence Way Princeton, N J 08540 It has recently been shown that gradient descent learning algorithms for recurrent neural networks can perform poorly on tasks that involve long-term dependencies. In this paper we explore this problem for a class of architectures called NARX n...

NarX-NarL and NarQ-NarP are paralogous two-component regulatory systems that control Escherichia coli gene expression in response to the respiratory oxidants nitrate and nitrite. Nitrate stimulates the autophosphorylation rates of the NarX and NarQ sensors, which then phosphorylate the response regulators NarL and NarP to activate and repress target operon transcription. Here, we investigated b...

Anaerobic respiratory gene expression in Escherichia coli is differentially controlled by nitrate and nitrite through dual interacting two-component regulatory systems. The NarX sensor is one of two membrane-spanning sensor kinases that control the phosphorylation state of two DNA-binding response regulators. We have studied NarX autophosphorylation in crude membrane preparations from cells tha...

Recently, fully connected recurrent neural networks have been proven to be computationally rich—at least as powerful as Turing machines. This work focuses on another network which is popular in control applications and has been found to be very effective at learning a variety of problems. These networks are based upon Nonlinear AutoRegressive models with eXogenous Inputs (NARX models), and are ...

Foreign exchange market is one of the most complex dynamic market with high volatility, non linear and irregularity. As the globalization spread to the world, exchange rates forecasting become more important and complicated. Many external factors influence its volatility. To forecast the exchange rates, those external variables can be used and usually chosen based on the correlation to the pred...

algorithm [3]. A method is presented for calculating the Higher-order In this paper, the method of Way and Green [2] will Frequency Response Functions (HFRFs) of NARX neural be extended to the frequency-domain. By harmonically networks. HFRFs are the Fourier transforms of Volterra probing the network equation, the HFRFs of the network kernels and can be viewed as multi-dimensional equivawill be...

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...