Multi-dimensional data classification is an important and challenging problem in many astro-particle experiments. Neural networks have proved to be versatile and robust in multi-dimensional data classification. In this article we shall study the classification of gamma from the hadrons for the MAGIC Experiment. Two neural networks have been used for the classification task. One is Multi-Layer P...

We present a method that uses competitive learning and a neighbourhood function in a similar way to the self-organising map (SOM) [3]. The network consists of a number of modules that are positioned in an array (normally in one or two dimensions) where each module performs a subspace projection and the rotation of these subspaces is weighted by the neighbourhood function. Non-linear activation ...

In this paper the capability of using self-organising neural maps (SOM) as music style classifiers from symbolic specifications of musical fragments is studied. From MIDI file sources, the monophonic melody track is extracted and cut into fragments of equal length. From these sequences, melodic, harmonic, and rhythmic numerical descriptors are computed and presented to the SOM. Their performanc...

In this paper the capability of using self-organising neural maps (SOM) as music style classifiers of musical fragments is studied. From MIDI files, the monophonic melody track is extracted and cut into fragments of equal length. From these sequences, melodic, harmonic, and rhythmic numerical descriptors are computed and presented to the SOM. Their performance is analysed in terms of separabili...

In order to have an autonomous robot, the robot must be able to navigate independently within an environment. Place cells are cells that respond to the environment the animal is in. In this paper we present a model of place cells based on Self Organising Maps. The aim of this paper is to show that localisation can be performed even without having a built in map. The model presented shows that t...

The Self-Organising Map is a popular unsupervised neural network model which has been used successfully in various contexts for clustering data. Even though labelled data is not required for the training process, in many applications class labelling of some sort is available. A visualisation uncovering the distribution and arrangement of the classes over the map can help the user to gain a bett...

The hierarchical abstraction of a Web site is useful in organising information and reducing the number of alternatives that must be considered at any one time when browsing the site. We present such an abstraction, which is computed from a user’s query and a Web site. A Web site is viewed as a directed graph with Web nodes and Web arcs, where the Web nodes correspond to HTML files (i.e., Web pa...

Mixed mode oscillations (MMOs) are complex oscillatory waveforms that naturally occur in physiologically relevant dynamical processes. MMOs were studied in a model of electrical bursting in a pituitary lactotroph [34] where geometric singular perturbation theory and bifurcation analysis were combined to demonstrate that the MMOs arise from canard dynamics. In this work, we extend the analysis d...

In this paper we present a landmark based navigation mechanism for a mobile robot. The system uses a self-organising mechanism to map the environment as the robot is led around that environment by an operator. Detected landmarks, and their relative position towards each other, are recorded in a map that can subsequently be used to plan and execute paths from the robot's current location to a `g...