Zamani, M;
Salinna, A;
Andreas, DD;
(2020)
Dictionary Construction for Accurate and Low-Cost Subspace Learning in Unsupervised Spike Sorting.
In:
Proceedings of the UKSim-AMSS 22nd International Conference on Computer Modelling and Simulation, UKSim2020.
EDAS
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Abstract
This paper discusses and outlines the construction of highly reliable and power efficient dictionaries as the main block in unsupervised feature learning from evolving sub-spaces. Three types of dictionaries are considered in this paper for unsupervised subspace learning including Hadamard φ_(H_h (k) ), equiangular tight frame φ_ETF(k) and random Bernoulli φ_Bern(k) . The constructed dictionaries are then utilized in unsupervised feature learning algorithm and the classification results are investigated using a library-based neural simulator consists of various noise levels and 300 different average spike shapes. The proposed dictionaries obtain high performance with classification error of around 7% over 100 windows of generated data using the developed neural signals for 3 to 6 clusters and noise levels σ_N between 0.05 and 0.3. In summary, the combination of constructed dictionaries and subspace learning present a new class of implantable feature extractors robust to extreme signal variations and well-suited for hardware implementation.
| Type: | Proceedings paper |
|---|---|
| Title: | Dictionary Construction for Accurate and Low-Cost Subspace Learning in Unsupervised Spike Sorting |
| Event: | International Conference on Computer Modelling and Simulation (UKSim) |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://doi.org/10.5013/IJSSST.a.21.02.12 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10094601 |
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