NDLI: Improved margin multi-class classification using dendritic neurons with morphological learning

Content Provider	IEEE Xplore Digital Library
Author	Hussain, S. Shih-Chii Liu Basu, A.
Copyright Year	2014
Description	Author affiliation: Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore (Hussain, S.; Basu, A.) \|\| Inst. of Neuroinf., Univ. of Zurich, Zurich, Switzerland (Shih-Chii Liu)
Abstract	We present an architecture of a spike based multiclass classifier using neurons with non-linear dendrites and sparse synaptic connectivity where each synapse takes a binary value. The learning in this model happens not through weight updates but through structural changes, i.e. a change of connectivity between inputs and dendrites. Hence, it is well suited for implementation in neuromorphic systems using address event representation (AER). We present a new learning rule that allows better generalization of the system to noisy testing data making it feasible to transfer learnt weights in software to a hardware device interfacing with noisy spiking sensors. The new rule improves testing accuracy by 7 - 10% compared to earlier versions. We also present preliminary results for multi-class classification on handwritten digits from the MNIST database and show that our system can attain comparable performance (≈ 3% more error) with other reported spike based classifiers while using at least 50% less synaptic resources.
Sponsorship	IEEE Circuits Syst. Soc.
Starting Page	2640
Ending Page	2643
File Size	772693
Page Count	4
File Format	PDF
e-ISBN	9781479934324
DOI	10.1109/ISCAS.2014.6865715
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-01
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Testing Neurons Computer architecture Accuracy Microprocessors Vectors
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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