Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks

Summary

Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks is a doctoral thesis^[1].

Key Facts

• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks authored Kshitij Dhoble^[2].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's instance of is recorded as doctoral thesis^[3].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks was published by Tuwhera Open Access Publisher^[4].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's language of work or name is recorded as English^[5].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's country of origin is recorded as New Zealand^[6].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks was released on 2013^[7].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's main subject is machine learning^[8].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's main subject is liquid state machine^[9].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's title is recorded as Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks^[10].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's copyright holder is recorded as Kshitij Dhoble^[11].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's thesis submitted to is recorded as Auckland University of Technology^[12].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's on focus list of Wikimedia project is recorded as NZThesisProject^[13].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's copyright status is recorded as copyrighted^[14].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's thesis committee member is recorded as Nikola Kasabov^[15].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's thesis committee member is recorded as Giacomo Indiveri^[16].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's thesis submitted for degree is recorded as Doctor of Philosophy^[17].

Body

Authorship and Creation

Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks authored Kshitij Dhoble^[2]. It was published by Tuwhera Open Access Publisher^[4].

Publication

Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks was published on 2013^[7]. Its language of work or name is recorded as English^[5].

Subject and Themes

Main subjects include machine learning^[8] and liquid state machine^[9].