Optimal connectivity in hardware-targetted MLP networks

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2009, Pages 2619-2626

  Rast, A D ^a   Welbourne, S ^a   Jin, X ^a   Furber, S B ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVATION FUNCTIONS; ADAPTIVITY; COMPONENT FAILURES; DESIGN TIME; DIFFERENT SIZES; ERROR OSCILLATION; FIXED NUMBERS; GAIN SETTINGS; GAIN VALUES; HARDWARE IMPLEMENTATIONS; HARDWARE RESOURCES; NETWORK DESIGN; NETWORK SIMULATION; NETWORK SIMULATORS; NETWORK SIZE; NEURAL CHIPS; OPTIMAL CONNECTIVITY; OPTIMAL VALUES; PRELIMINARY ANALYSIS; SOFTWARE ENVIRONMENTS; TARGETTING; TEST RESULTS; THEORETICAL MODELS; TRAINING TIME;

HARDWARE; LENSES; NEURAL NETWORKS; NEURONS; OPTICAL INSTRUMENTS; OPTIMIZATION; QUALITY ASSURANCE;

SIMULATORS;

EID: 70449431386     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2009.5178831     Document Type: Conference Paper

References (13)

1. J. C. Reijneveld, S. Ponten, H. Berendse, and C. J. Stam, "The application of graph theoretical analysis to complex networks in the brain, " Clinical Neurophysiology, vol. 118, no. 11, Nov. 2007.
2. J. KrishnaKumar, "Optimization of the neural net connectivity pattern using a backpropagation algorithm, " Neurocomputing, vol. 5, no. 6, Nov. 1993.
3. A. Rast, S. Yang, M. M. Khan, and S. Furber, "Virtual synaptic interconnect using an asynchronous network-on-chip, " in Proc. 2008 Int'l Joint Conf. on Neural Networks (IJCNN2008), 2008.
4. M. M. Khan, D. Lester, L. Plana, A. Rast, X. Jin, E. Painkras, and S. Furber, "SpiNNaker: Mapping neural networks onto a massivelyparallel chip multiprocessor, " in Proc. 2008 Int'l Joint Conf. on Neural Networks (IJCNN2008), 2008.
5. D. J. Watts and S. Strogatz, "Collective dynamics of 'small-world' networks, " Nature, vol. 393, no. 6684, Jun. 1998.
6. O. Shefi, I. Golding, R. Segev, E. Ben-Jacob, and A. Ayali, "Morphological characterization of in vitro neuronal networks, " Phys. Review E, vol. 66, no. 2, Aug. 2002.
7. N. Davey, L. Calcroft, and R. Adams, "High capacity, small world associative memory models, " Connection Science, vol. 18, no. 3, Sep. 2006.
8. J. J. Torres, M. A. Muñoz, J. Marro, and P. L. Garrido, "Influence of topology on the performance of a neural network, " Neurocomputing, vol. 58-60, no. 6, Nov. 2004.
9. L. Calcroft, R. Adams, and N. Davey, "Efficient architectures for sparsely-connected high capacity associative memory models, " Connection Science, vol. 19, no. 2, Jun. 2007.
10. D. Simard, L. Nadeau, and H. Kroger, "Fastest learning in small-world neural networks, " Phys. Letters A, vol. 336, no. 1, Jan. 2005.
11. L. Maguire, T. M. McGinnity, B. Glackin, A. Ghani, A. Belatreche, and J. Harkin, "Challenges for large-scale implementations of spiking neural networks on FPGAs, " Neurocomputing, vol. 71, no. 1-3, Dec. 2007.
12. D. L. T. Rohde, "LENS: The light, efficient network simulator, " From http://tedlab. mit. edu/~dr/Lens, 1999.
13. S. Welbourne and M. A. L. Ralph, "Using parallel distributed processing models to simulate phonological dyslexia: The key role of plasticity related recovery, " J. Cognitive Neuroscience, vol. 19, no. 7, Jul. 2007.