A number of algorithms has been proposed for extending ABR congestion avoidance algorithms in ATM networks to perform feedback consolidation at the branch points of multicast connections. Schemes that attempt to maxim...
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In this work the kernel Adaline algorithm is presented. The new algorithm is a generalisation of Widrow's and Hoff's linear Adaline, and allows to approximate non-linear functional relationships. Similar to th...
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An investigation into the parametric and non-parametric modelling of a two dimensional flexible plate structure is presented in this paper. The parametric approaches obtaining linear parametric models of the system us...
An investigation into the parametric and non-parametric modelling of a two dimensional flexible plate structure is presented in this paper. The parametric approaches obtaining linear parametric models of the system using recursive least squares and genetic algorithms. The non-parametric models of the system are developed using a non-linear AutoRegressive process with eXogeneous input model with multi-layered perceptron neural networks, Elman recurrent neural networks and adaptive neuro-fuzzy inference systems. The models are validated using several validation tests including input-output mapping, mean squares of error and correlation tests. A comparative assessment of the techniques used is presented and discussed in terms of accuracy, efficiency and performance in estimating the modes of vibration of the system.
In this paper a visual self-localization method for a humanoid robot is presented. This one is based on monocular information. The goal of this method is to obtain the position (x;y) and orientation θ of the humanoid...
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The purpose of this article is to perform a comparison between two identification models: a nonlinear one referred to as HARMAX and a classical linear one, of Box-Jenkins (BJ) type. The first model modifies a classica...
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Multiway Principal Component Analysis (MPCA) and Case-Based Reasoning (CBR) approaches are applied in a biological nutrient removal process. The goal of this study was to monitor of normal and abnormal operation condi...
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This paper presents a single multiplicative neuron model based on a polynomial architecture. The proposed neuron model consists of a non-linear aggregation function based on the concept of generalized mean of all mult...
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computer-aided design of controlsystems via multi-objective optimisation is a computationally demanding task that may benefit from parallel processing techniques. In this paper, we report on a new parallel processing...
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computer-aided design of controlsystems via multi-objective optimisation is a computationally demanding task that may benefit from parallel processing techniques. In this paper, we report on a new parallel processing gateway that supports the use of parallel processing within the framework of an existing computer-aided control system design software package. In many control system design exercises which employ optimisation, the bulk of the computational effort is devoted to the evaluation of the objectives of the optimisation at each iteration. This paper demonstrates, with an example, how, using the gateway, parallel processing can be used within the framework of existing computer-aided control system design tools to compute these objective values.
The paper describes an extension to a standard, block-structured, interactive simulation language in which colours are used to indicate the levels of variables in the simulated process. A coding system is used to clas...
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The paper describes an extension to a standard, block-structured, interactive simulation language in which colours are used to indicate the levels of variables in the simulated process. A coding system is used to classify the level of simulated process variables into three regions of safe, unsafe and dangerous operation, represented by green, yellow and red colours respectively. The enhanced simulation package facilitates controller development for industrial plant and avoids dangerous levels being overlooked in the simulation of prototype systems prior to their implementation on plant. The use of enhanced facility is demonstrated by simulation of the electrode drive system and controller for an electric arc furnace.
The goal of this study was to examine the ability of Neural Networks to recognise the levels of anaesthetic state of a patient. Data obtained under different levels of anaesthesia have been modelled for the purpose. I...
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The goal of this study was to examine the ability of Neural Networks to recognise the levels of anaesthetic state of a patient. Data obtained under different levels of anaesthesia have been modelled for the purpose. It is shown that inferential parameters can be used to recognise the levels of anaesthesia. In addition to demonstrating the ability of neural networks for classification we were interested in understanding the classification strategy discovered by the neural networks. Multivariate data analysis techniques, namely Principal Components Analysis and Canonical Discriminant Variates, were applied to analyse the resultant networks. (C) 1997 Elsevier Science B.V.
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