Abstract: In this paper the stochastic complexity criterion is applied to estimation of the order in AR and ARMA models. The power of the criterion for short strings is illustrated by simulations. It requires an integral of the square root of Fisher information, which is done by Monte Carlo technique. The stochastic complexity, which is the negative logarithm of the Normalized Maximum Likelihoo...

The aim of this paper is the presentation of time-variant spectrograms of surface EMG signals to estimate fatigue processes in muscle and to consider recruitments of motor units. For this we used techniques on the base of ARMA and AR models. We illustrate our applications by three examples: influence of training to maximal and explosive isometric contraction, fatigue processes in an all-out cyc...

Despite their theoretical limitations, ARIMA models are widely used in real-life forecasting tasks. Parzen has proposed an extension of ARIMA models: ARARMA models. ARARMA models consist of an AR model followed by an ARMA model. Following Parzen approach,-NARMA neural network are MLP, the units of which are simple non-linear ARMA-based models (-NARMA units). They are a non-linear extension of A...

عوامل متعددی بر روند تاثیرگذاری نگاره های ایران شبه قاره هند در دوران حکومت مغولان موثر بوده است. موضوع این پژوهش بررسی نگارگری دوره با منابع کتابخانه ای و بکارگیری روش توصيفی- تحليلی رویکرد تاریخی، آثار از منظر شیوه پیدایش، ساختار، خصایص صوری تاثیرپذیری هنر ایرانی مورد قرار گرفته ‏است. اساس نتایج پژوهش، عصر مغولان، به گونه چشم گیر معرف نفوذ طور کلی، گرایش هنرمندان مغول هنرهای تصویری ایران‏ قوا...

With China's continuous opening to the outside world, changes in international environment and operation of cross-border RMB settlement system (CIPS), scale has fluctuated continuously. In response this phenomenon, authors collected sorted out total amount payments from 2011 2020 time sequence data China, then use five AR models including ARMA, GARCH(1.1), EGARCH(1.1), PARCH(1.1), CARCH(1.1) fi...

In this paper, a parallel identification and restoration procedure is described for images with symmetric, noncausal blurs. It is shown that the identification problem can be specified as a parallel set of one-dimensional complex autoregressive moving-average (ARMA) identification problems. By expressing the ARMA models as equivalent infiniteorder autoregressive (AR) models, an entirely linear ...

The Kalman filter is a well-known and efficient recursive algorithm that estimates the state of a dynamic system from a series of indirect and noisy observations of this state. Its applications range from signal processing to machine learning, through speech processing or computer vision. The underlying model usually assumes white noises. Extensions to colored autoregressive (AR) noise model ar...

In this paper, novel techniques in increasing the accuracy and speed of convergence of a Feed forward Back propagation Artificial Neural Network (FFBPNN) with polynomial activation function reported in literature is presented. These technique was subsequently used to determine the coefficients of Autoregressive Moving Average (ARMA) and Autoregressive (AR) system. The results obtained by introd...