The remainder of this paper is organised as follows. In the following section we will briefly describe the test environment of the system. Particularly, we will summarize the approach to acquire the input data for the connectionist part of the system. Next, we will provide a description of the artificial neural network model, namely the self-organising feature map, and its application to legal ...

This paper presents a novel self organising neural network It has been developed for use as a simpli ed model of cortical development Unlike many other models of topological map formation all synaptic weights start at zero strength so that synaptogenesis might be modelled In addition the algorithm works with the same format of encoding for both inputs to and outputs from the network so that the...

Metagenomic projects using whole-genome shotgun (WGS) sequencing produces many unassembled DNA sequences and small contigs. The step of clustering these sequences, based on biological and molecular features, is called binning. A reported strategy for binning that combines oligonucleotide frequency and self-organising maps (SOM) shows high potential. We improve this strategy by identifying suita...

Analysing human gait has found considerable interest in recent computer vision research. So far, however, contributions to this topic exclusively dealt with the tasks of person identification or activity recognition. In this paper, we consider a different application for gait analysis and examine its use as a means of deducing the physical well-being of people. The proposed method is based on t...

Metagenomic projects using whole-genome shotgun (WGS) sequencing produces many unassembled DNA sequences and small contigs. The step of clustering these sequences, based on biological and molecular features, is called binning. A reported strategy for binning that combines oligonucleotide frequency and self-organising maps (SOM) shows high potential. We improve this strategy by identifying suita...

MR Imaging techniques provide a non-invasive and accurate method for determining the ultra-structural features of human anatomy. In this study, we utilise a novel approach to segment out the ventricular system in a series of high resolution T1-weighted MR images. Our approach is based on an automated landmark extraction algorithm which automatically selects points along the contour of the ventr...

In this paper it is shown how to map a data manifold into a simpler form by progressively discarding small degrees of freedom. This is the key to self-organising data fusion, where the raw data is embedded in a very high-dimensional space (e.g. the pixel values of one or more images), and the requirement is to isolate the important degrees of freedom which lie on a low-dimensional manifold. A u...

In the past few years, various variants of the self-organising map (SOM) have been proposed to extend its ability for modelling timeseries or temporal sequence. Most of them, however, have little connection to, or are over-simplified, autoregressive (AR) models. In this paper, a new extension termed, self-organising mixture autoregressive (SOMAR) network is proposed to topologically cluster tim...

This paper uses the Kohonen Self-Organising Map (KSOM) to detect, diagnose, and classify induction motor faults. A series of simulations using models 3-phase based on real industrial parameters were performed MATLAB/Simulink under fault conditions such as inter-turn, power frequency variation, over-voltage unbalance in supply voltage. The model was trained input signals various conditions. Vari...

The problem of obtaining an accurate forecast is becoming more and more significant as the production possibilities and technologies evolve. The accuracy of a forecast mainly depends on the dataset used for forecasting as well as on the methods employed. This study is devoted to the time series analysis. A set of known methods and techniques are used for analysing the time series; one of them i...