In this paper, the performance of different predictive vector quantization (PVQ) structures is studied and compared for different degrees of channel noise. Predictive quantization schemes with an auto-regressive (AR) decoder structure are compared with schemes that employ a moving average (MA) decoder. For noisy channels MA prediction performs better than AR. It is shown here that a combination...

To investigate the variability in energy output from a network of photo-voltaic cells, solar radiation was recorded at ten sites every ten minutes in the Pentland Hills to the south of Edinburgh. We identify spatio-temporal auto-regressive moving average (STARMA) models as the most appropriate to address this problem. Although previously considered computationally prohibitive to work with, we s...

The paper considers the development of a new type of artificial neural network and its applicability to non-linear system identification. This is the functional-link neural network with internal dynamic elements. The net consists of a single layer where the nonlinearity is firstly introduced by enhancing the input pattern with a functional expansion. The internal dynamic elements are auto-regre...

A definition of reliability appropriate for systems containing significant software that includes trustworthiness and is independent of requirements will be stated and argued for. The systems addressed will encompass the entire product development process as well as both product and its documentation. Cost incurred as a result of faults will be shown to be appropriate as a performance measureme...

Abstract Life expectancy at birth (LEB) is a major factor for decision-making bodies when developing new healthcare policies or improving existing ones. This paper, with the help of R language, processes and examine LEB data in Saudi Arabia from 1960 to 2012 using time-series analysis. To test validity model, 2013 2018 are used. The performance selected auto regressive integrated moving average...

This paper presents a method to simulate the growth of the facial/head model of a person from childhood to adulthood. The method works by generating continuous data of standard landmarks using auto-regressive moving average based on anthropometry of the head/face. The standard landmarks are assigned to the particular head and face, and vertices of the growing head/facial model are calculated by...

In this paper a new least-squares (LS) approach is used to model the discrete-time fractional differintegrator. This approach is based on a mismatch error between the required response and the one obtained by the difference equation defining the auto-regressive, moving-average (ARMA) model. In minimizing the error power we obtain a set of suitable normal equations that allow us to obtain the AR...

Wide-spread real-time applications make it necessary for service providers to guarantee QoS parameters. This requires precise forecast of network traffic. A possible method of the forecast is measuring traffic then analyzing it and fitting model to the measured data, finally predicting the observed parameter using the fitted model. The efficiency of the prediction is decreased by outlying sampl...

We invoke an auto-regressive IIR inverse model for convolutive ICA and derive expressions for the likelihood and its gradient. We argue that optimization will give a stable inverse. When there are more sensors than sources the mixing model parameters are estimated in a second step by least squares estimation. We demonstrate the method on synthetic data and finally separate speech and music in a...