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Pair-associate learning with modulated spike-time dependent plasticity


Yusoff, Nooraini and Grüning, André and Notley, Scott (2012) Pair-associate learning with modulated spike-time dependent plasticity. In: Artificial Neural Networks and Machine Learning – ICANN 2012. Lecture Notes in Computer Science, 7552 (7552). Springer, pp. 137-144. ISBN 978-3-642-33268-5

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Abstract

We propose an associative learning model using reward modulated spike-time dependent plasticity in reinforcement learning paradigm. The task of learning is to associate a stimulus pair, known as the predictor−choice pair, to a target response.In our model, a generic architecture of neural network has been used, with minimal assumption about the network dynamics.We demonstrate that stimulus-stimulus-response association can be implemented in a stochastic way within a noisy setting.The network has rich dynamics resulting from its recurrent connectivity and background activity. The algorithm can learn temporal sequence detection and solve temporal XOR problem.

Item Type: Book Section
Additional Information: Book Subtitle: 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part I
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: College of Arts and Sciences
Depositing User: Dr. Nooraini Yusoff
Date Deposited: 26 Oct 2014 03:04
Last Modified: 26 Oct 2014 03:04
URI: http://repo.uum.edu.my/id/eprint/12489

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