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's publisher is recorded as 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's publication date is recorded as +2013-00-00T00:00:00Z^[7].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's main subject is recorded as machine learning^[8].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's main subject is recorded as liquid state machine^[9].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's Handle ID is recorded as 10292/5643^[10].
• 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^[11].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's copyright holder is recorded as Kshitij Dhoble^[12].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's thesis submitted to is recorded as Auckland University of Technology^[13].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's on focus list of Wikimedia project is recorded as NZThesisProject^[14].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's copyright status is recorded as copyrighted^[15].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's thesis committee member is recorded as Nikola Kasabov^[16].
• Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's thesis committee member is recorded as Giacomo Indiveri^[17].

Body

Designation and Status

Spatio-/spectro-temporal pattern recognition using evolving probabilistic spiking neural networks's instance of is recorded as doctoral thesis^[3].