We present an on-line method for detecting changes and estimating parameters in AR(X) models. The method is based on the assumption of piecewise constant parameters resulting in a sparse structure of their derivative. To illustrate the algorithm and its performance, we apply it to the change in the model parameters of some ARX models. The example illustrates that the new method shows good perfo...

In this study, an ARX model with nonparametric multi time scale regression model was proposed for short term gust forecasting and applied to a ski resort in Japan. Proposed ARX model can be used for short term forecasting of mean and fluctuating wind speed. Proposed nonparametric multi time scale regression model can appropriately estimate the peak factor and shows better agreement with the mea...

The man-machine cooperative system is attracting great attention in many fields, such as industry, welfare and so on. The assisting system must be designed so as to accommodate the operator’s skill, which might be strongly affected by the fatigue. This paper presents a new fatigue recognizer based on the Electro MyoGram (EMG) signals and the Stochastic Switched ARX (SS-ARX) model which is one o...

Quantitative modeling is an important tool for research on complex physiological systems. Mathematical model are playing important role in analyzing complex system. In order to create an accurate model and significant interpretations, system identification techniques are needed. An optimized auto-regressive model based on Sequential Genetic algorithm (Sequential GA) is investigated in this stud...

A smooth nonlinear system identification method without resorting to on-line parameter estimation is presented. Based on the radial basis function, a signal-dependent ARX (RBF-ARX) model is established to describe the nonlinear system dynamics. Especially, a new structured nonlinear parameter optimization algorithm based on the Levenberg-Marquardt algorithm and the least squares method is propo...

BACKGROUND The extraction of the middle latency auditory evoked potentials (MLAEP) is usually done by moving time averaging (MTA) over many sweeps (often 250-1,000), which could produce a delay of more than 1 min. This problem was addressed by applying an autoregressive model with exogenous input (ARX) that enables extraction of the auditory evoked potentials (AEP) within 15 sweeps. The objecti...

In the Prediction Error identification framework, it is crucial that collected data are informative with respect to chosen model structure get a consistent estimate. this work, we focus on informativity property for of multi-inputs single-output ARX systems in closed-loop and derive necessary sufficient condition verify if given multisine external excitation combined feedback introduced by cont...

We report the comprehensive identification of periodic genes and their network inference, based on a gene co-expression analysis and an Auto-Regressive eXogenous (ARX) model with a group smoothly clipped absolute deviation (SCAD) method using a time-series transcriptome dataset in a model grass, Brachypodium distachyon. To reveal the diurnal changes in the transcriptome in B. distachyon, we per...

Mutations in the aristaless-related homeobox (ARX) gene are associated with multiple neurologic disorders in humans. Studies in mice indicate Arx plays a role in neuronal progenitor proliferation and development of the cerebral cortex, thalamus, hippocampus, striatum, and olfactory bulbs. Specific defects associated with Arx loss of function include abnormal interneuron migration and subtype di...