In this paper, a perceptron-based algorithm for fusion of multiple fingerprint matchers is presented. The person to be identified submits to the personal authentication system her/his fingerprint and claimed identity. Multiple fingerprint matchers provide a set of verification scores, that are then fused by a single-layer perceptron with class-separation loss function. Weights of such perceptro...

In this paper, both the architecture and learning procedure underlying the parallel layer perceptron is presented. This topology, di1erent to the previous ones, uses parallel layers of perceptrons to map nonlinear input–output relationships. Comparisons between the parallel layer perceptron, multi-layer perceptron and ANFIS are included and show the e1ectiveness of the proposed topology. c © 20...

it has been demonstrated that anxiety is accompanied by significant warm up in the periorbital area. this warm up was attributed to the increased blood circulation in the area around the eyes. the whole pattern makes physiological and evolutionary sense since it represents a mechanism to facilitate rapid eye movements during preparedness for fight. this increased blood flow dissipates convectiv...

This paper presents a comparison of different machine learning algorithms applied to automatic sleep detection which uses electroencephalogram signals as a differentiating basis. The Single-Layer Perceptron, Multi-Layer Perceptron, Support Vector Machine, Boosted Tree and the Multi-Agent (comprising of the earlier models) models are developed and analyzed with training and testing datasets. The...

Difficult non-linear problems can be mapped to a set of localised linear problems. A self-organising map (SOM) is used as a gating function to a localised mixture of experts classifier and is shown to find solutions equivalent to those learned by a multi-layer perceptron while retaining the simplicity and resilience of a single-layer perceptron. Modifications to the traditional softmax gate fun...

background: brain tissue segmentation for delineation of 3d anatomical structures from magnetic resonance (mr) images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (gm), white matter (wm) and cerebrospinal fluid (csf), but only if the obtained segmentation results are correct. due to image arti...

A nonlinearity is required before matched filtering in mInimum error receivers when additive noise is present which is impulsive and highly non-Gaussian. Experiments were performed to determine whether the correct clipping nonlinearity could be provided by a single-input singleoutput multi-layer perceptron trained with back propagation. It was found that a multi-layer perceptron with one input ...

It is well known that a two-layer perceptron network with threshold neurons is incapable of forming arbitrary decision regions in input space, while a three-layer perceptron has that capability. The effect of replacing the output neuron in a two-layer perceptron with a bithreshold element is studied. The limitations of this modified two-layer perceptron are observed. Results on the separating c...

In this study, we propose a multi-layer perceptron with a glial network which is inspired from the features of glias in the brain. All glias in the proposed network generate independent oscillations, and the oscillations propagate through the glial network with attenuation. We apply the proposed network to the two-spiral problem. Computer simulations show that the proposed network gains a bette...

this study shows the usefulness of artificial neural network (ann) in maintenance planning and man-agement. an ann model based on the multi-layer perceptron having three hidden layers and four processing elements per layer was built to predict the expected downtime resulting from a breakdown or a maintenance activity. the model achieved an accuracy of over 70% in predicting the expected downtime.