Kalman filter (KF) can provide optimal solutions if the system dynamic and measurement models are correctly defined, and the noise statistics for the measurement and system are completely known. The conventional way of determining the covariance matrices of process noise and observation errors relies on analysis of empirical data from each sensor in a system, which is called KF tuning. In pract...

Compared to the conventional methods, Artificial Neural Networks (ANN) are considered to be one of the reliable tools for modeling of complex phenomena such as demand. Aim of this study is to provide a model for gasoline demand in transportation section of Tehran metropolis through multilayered perceptron neural network and using the presented model in analyzing the sensitivity of the model to ...

Artificial neural network was considered in previous studies for prediction of engine performance and emissions. ICA methodology was inspired in order to optimize the weights of multilayer perceptron (MLP) of artificial neural network so that closer estimation of output results can be achieved. Current paper aimed at prediction of engine power, soot, NOx, CO2, O2, and temperature with the ai...

We consider estimation of covariance matrices of stationary processes. Under a short-range dependence condition for a wide class of nonlinear processes, it is shown that the banded covariance matrix estimates converge in operator norm to the true covariance matrix with explicit rates of convergence. We also establish the consistency of the estimate of the inverse covariance matrix. These result...

this paper presents the application of three main artificial neural networks (anns) in damage detection of steel bridges. this method has the ability to indicate damage in structural elements due to a localized change of stiffness called damage zone. the changes in structural response is used to identify the states of structural damage. to circumvent the difficulty arising from the non-linear n...

Bottleneck (BN) feature has attracted considerable attentions by its capacity of improving the accuracies in speech recognition tasks. Recently, researchers have proposed some modified approaches for extracting more effective BN feature, but these approaches still need further improvement. In this paper, motivated by both deep belief networks (DBN) and hierarchical Multilayer Perceptron (MLP), ...

The training algorithm studied in this paper is inspired by the biological metaplasticity property of neurons. Tested on different multidisciplinary applications, it achieves a more efficient training and improves Artificial Neural Network Performance. The algorithm has been recently proposed for Artificial Neural Networks in general, although for the purpose of discussing its biological plausi...

An artificial neural network has been used to determine the volume flux and rejections of Ca2+ , Na+ and Cl¯, as a function of transmembrane pressure and concentrations of Ca2+, polyethyleneimine, and polyacrylic acid in water softening by nanofiltration process in presence of polyelectrolytes. The feed-forward multi-layer perceptron artificial neural network including an eight-neuron hidde...