Iain Strachan

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The standard GTM (generative topographic mapping) algorithm assumes that the data on which it is trained consists of independent, identically distributed (i.i.d.) vectors. For time series, however, the i.i.d. assumption is a poor approximation. In this paper we show how the GTM algorithm can be extended to model time series by incorporating it as the(More)
The tokamak is currently the principal magnetic confinement system for controlled fusion research. In seeking to understand the physics of the high temperature plasma inside the tokamak, it is important to have detailed information on the spatial distribution of electron density. One technique for density measurement uses laser interferometry, which gives(More)
BACKGROUND Reliable, automated QT analysis would allow the use of all the ECG data recorded during continuous Holter monitoring, rather than just intermittent 10-second ECGs. METHODS BioQT is an automated ECG analysis system based on a Hidden Markov Model, which is trained to segment ECG signals using a database of thousands of annotated waveforms. Each(More)
BACKGROUND Existence of a relationship between the electrocardiographic QRS interval duration and the diurnally varying heart rate, of consistent sign and magnitude, is controversial and the relationship has not been fully characterized in normal populations. METHODS AND RESULTS We analyzed the QRS-RR interval relationship in 884 Holter recordings in 410(More)
This is the User s Guide to the GTM Toolbox a set of Matlab functions and scripts that implements and demonstrates the generative topographic mapping a method for density modelling dimensionality reduction and data visualisation This document gives a brief description of the GTM the content of the toolbox and what is required to use it It describes how to(More)
The standard GTM (generative topographic mapping) algorithm assumes that the data on which it is trained consists of independent, identically distributed (i.i.d.) vectors. For time series, however, the i.i.d. assumption is a poor approximation. In this paper we show how the GTM algorithm can be extended to model time series by incorporating it as the(More)
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