By Toshinori Deguchi, Junya Fukuta, Naohiro Ishii (auth.), Marco Tomassini, Alberto Antonioni, Fabio Daolio, Pierre Buesser (eds.)

The booklet constitutes the refereed complaints of the eleventh overseas convention on Adaptive and typical Computing Algorithms, ICANNGA 2013, held in Lausanne, Switzerland, in April 2013.
The fifty one revised complete papers offered have been conscientiously reviewed and chosen from a complete of ninety one submissions. The papers are geared up in topical sections on neural networks, evolutionary computation, tender computing, bioinformatics and computational biology, complex computing, and applications.

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Additional info for Adaptive and Natural Computing Algorithms: 11th International Conference, ICANNGA 2013, Lausanne, Switzerland, April 4-6, 2013. Proceedings

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Power spectra during (top)/after (bottom) STDP, with (R)/without (L) scaling Alzheimer’s disease [19–21], and further understanding of this mechanism and its relationship to learning and disease pathology may be crucial to finding better treatments. We also showed that scaling does not negatively affect the network at baseline, but that it is stable. We demonstrated that E→E scaling is sufficient to balance the hyper-potentiation caused by unrestrained STDP. Potentiation strengthens the co-incident connections between neurons in a positive feedback cycle, eventually leading to hyper-potentiation, but scaling acts to shift the mean activation constantly back towards the target activity.

IEEE Trans. on Information Theory 44, 525–536 (1998) 19. : Gesamelte mathematische abhandlungen, Band 1 (1950) 20. : Probabilistic Methods in Combinatorics. Academic Press (1974) 21. : Dimension-independent rates of approximation by neural networks. , K´ arn´ y, M. ) Computer-Intensive Methods in Control and Signal Processing, pp. 261–270. Birkh¨ auser, Boston (1997) 22. : Neural net approximation. In: Narendra, K. ) Proc. 7th Yale Workshop on Adaptive and Learning Systems, pp. 69–72. Yale University Press (1992) 23.

Information-selectivity of beta-amyloid pathology in an associative memory model. Front. Comput. Neurosci. 6(2) (January 2012) 21. : Effects of Compensation, Connectivity and Tau in a Computational Model of Alzheimer’s Disease. In: Proc. IJCNN, pp. 543–550. IEEE (2011) 22. : Spike-timing dependent plasticity in inhibitory circuits. Frontiers in Synaptic Neuroscience 2 (2010) 23. : Why there are complementary learning systems in the hippocampus and neocortex: Insights from the successes and failures of connectionist models of learning and memory.

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Adaptive and Natural Computing Algorithms: 11th by Toshinori Deguchi, Junya Fukuta, Naohiro Ishii (auth.),
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