Artificial neural networks (ANNs) are flexible computing frameworks and universal approximators that can be applied to a wide range of time series forecasting problems with a high degree of accuracy. However, despite all advantages cited for artificial neural networks, their performance for some real time series is not satisfactory. Improving forecasting especially time series forecasting accur...

Penalized splines are widespread tools for the estimation of trend and cycle, since they allow a data driven estimation of the penalization parameter by the incorporation into a linear mixed model. Based on the equivalence of penalized splines and the Hodrick-Prescott filter, this paper connects the mixed model framework of penalized splines to the WienerKolmogorov filter. In the case that tren...

A stereo vision system for detecting 3D-objects is presented. The method uses a pair of externally uncalibrated cameras and is able t o detect objects located on a staircase. Detection is based on differencing stereo pair images, where a warping transform is used to overlay the left onto the right image, and vice versa. The 3D camera positions are obtained through model t~ased pose estimation a...

This correspondence addresses the asymptotic normal distribution of the sample mean and the sample covariance matrix of mixed spectra time series containing a sum of sinusoids and a moving average (MA) process. Two central limit (CL) theorems are proved. As an application of this result, the asymptotic normal distribution of any sinusoidal frequencies estimator of such time series based on seco...

Oil is the lifeblood of the industrial economy, oil prices are affected by many factors. China is a major industrial country, changes in the price of oil will affect many aspects of economic development, and therefore the price of crude oil research is extremely important. In this paper, monthly average prices of crude oil in Daqing from January 2000 to December 2010 are utilized to do the rese...

Object tracking is commonly used in video surveillance, but typically video with full frame rate is sent. We previously have shown that full frame rate is not needed, but it is unclear what the appropriate frame rate to send or whether we can further reduce the frame rate. This paper answers these questions for two commonly used object tracking algorithms (frame-differencing-based blob tracking...

We present a generalisation of the double long memory ARFIMA-FIGARCH model introducing time-varying memory coefficients both in the mean and in the variance. The model satisfies the empirical evidence of changing memory observed in average temperature series and can provide useful improvements in the forecasting, simulation and pricing issues related to weather derivatives. We provide an applic...

With advancements in machine-learning techniques, stock-price movements can ostensibly be forecasted using time-series data. In this study, several different types of long short-term memory (LSTM) are used to predict the closing prices Japanese stocks five days into future. Also, four features [i.e., simple moving average (SMA), linear weighted (WMA), exponential WMA (EMA), and Savitzky–Golay (...

This paper proposes new nonparametric hybrid exponentially weighted moving average (HEWMA) control charts based on simple random sampling (SRS) and ranked set (RSS) techniques using the Wilcoxon rank-sum W statistic. The in-control robustness out-of-co...