University of Hertfordshire Research Archive

        JavaScript is disabled for your browser. Some features of this site may not work without it.

        Browse

        All of UHRABy Issue DateAuthorsTitlesThis CollectionBy Issue DateAuthorsTitles

        Arkivum Files

        My Downloads
        View Item 
        • UHRA Home
        • University of Hertfordshire
        • Research publications
        • View Item
        • UHRA Home
        • University of Hertfordshire
        • Research publications
        • View Item

        Feature extraction from spectro-temporal signals using dynamic synapses, recurrency, and lateral inhibition

        Author
        Glackin, C.
        Maguire, L.
        McDaid, L.
        Attention
        2299/9626
        Abstract
        This paper presents a spiking neural network-based investigation of the issues associated with extraction of onset, offset, and coincidental firing features from spectro-temporal data. Speech samples containing spoken isolated digits from the TI46 database are employed to demonstrate the way in which these features can be extracted using leaky integrate-and-fire spiking neurons with dynamic synapses. The flexibility that the additional synaptic parameters in the neuron model provides, is demonstrated to be essential for onset, offset and coincidental firing extraction. Recurrency and the interaction between excitation and inhibition together with latency is demonstrated to be a viable means of extracting offset features. The effects of lateral inhibition and in particular its ability to induce transient synchrony in spike firing is evaluated. In particular, by defining a connection length parameter, and hence a neighbourhood size, synchronous firing is shown to gradually develop as connection length and neighbourhood size increases. Finally, the implications for this connectivity in spiking neural networks and its potential for learning spectral and spatio-temporal patterns via the formation of receptive fields is discussed
        Publication date
        2010
        Published in
        Neural Networks (IJCNN), The 2010 International Joint Conference on
        Published version
        https://doi.org/10.1109/IJCNN.2010.5596818
        Other links
        http://hdl.handle.net/2299/9626
        Metadata
        Show full item record
        Keep in touch

        © 2019 University of Hertfordshire

        I want to...

        • Apply for a course
        • Download a Prospectus
        • Find a job at the University
        • Make a complaint
        • Contact the Press Office

        Go to...

        • Accommodation booking
        • Your student record
        • Bayfordbury
        • KASPAR
        • UH Arts

        The small print

        • Terms of use
        • Privacy and cookies
        • Criminal Finances Act 2017
        • Modern Slavery Act 2015
        • Sitemap

        Find/Contact us

        • T: +44 (0)1707 284000
        • E: ask@herts.ac.uk
        • Where to find us
        • Parking
        • hr
        • qaa
        • stonewall
        • AMBA
        • ECU Race Charter
        • disability confident
        • AthenaSwan