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2018 | OriginalPaper | Buchkapitel

From von Neumann Architecture and Atanasoffs ABC to Neuro-Morphic Computation and Kasabov’s NeuCube: Principles and Implementations

verfasst von : Neelava Sengupta, Josafath Israel Espinosa Ramos, Enmei Tu, Stefan Marks, Nathan Scott, Jakub Weclawski, Akshay Raj Gollahalli, Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh, Kaushalya Kumarasinghe, Vivienne Breen, Anne Abbott

Erschienen in: Learning Systems: From Theory to Practice

Verlag: Springer International Publishing

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Abstract

During the 1940s John Atanasoff with the help of one of his students Clifford E. Berry, at Iowa State College, created the ABC (Atanasoff-Berry Computer) that was the first electronic digital computer. The ABC computer was not a general-purpose one, but still, it was the first to implement three of the most important ideas used in computers nowadays: binary data representation; using electronics instead of mechanical switches and wheels; using a von Neumann architecture, where the memory and the computations are separated. A new computational paradigm, named as Neuromorphic, utilises the above two principles, but instead of the von Neumann principle, it integrates the memory and the computation in a single module a spiking neural network structure. This chapter first reviews the principles of the earlier published work by the team on neuromorphic computational architecture NeuCube. NeuCube is not a general purpose machine but is still the first neuromorphic spatio/spectro-temporal data machine for learning, pattern recognition and understanding of spatio/spectro-temporal data. The chapter further presents the software/hardware implementation of the NeuCube as a development system for efficient applications on temporal or spatio/spectro-temporal across domain areas, including: brain data (EEG, fMRI), brain computer interfaces, robot control, multi-sensory data modelling, seismic stream data modelling and earthquake prediction, financial time series forecasting, climate data modelling and personalised, on-line risk of stroke prediction, and others. A limited version of the NeuCube software implementation is available from http://​www.​kedri.​aut.​ac.​nz/​neucube/​.

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Literatur
1.
Zurück zum Zitat David, B.: The Advent of the Algorithm: The 300-Year Journey From an Idea to the Computer. Houghton Mifflin Harcourt (2001) David, B.: The Advent of the Algorithm: The 300-Year Journey From an Idea to the Computer. Houghton Mifflin Harcourt (2001)
2.
Zurück zum Zitat Warren, S., McCulloch, Walter, P.: A logical calculus of the ideas immanent in nervous activity. Bull. Math. Biophy. 5(4), 115–133 (1943) Warren, S., McCulloch, Walter, P.: A logical calculus of the ideas immanent in nervous activity. Bull. Math. Biophy. 5(4), 115–133 (1943)
3.
Zurück zum Zitat LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436–444 (2015) LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436–444 (2015)
4.
Zurück zum Zitat Robert, R.S.: Moore’s law: past, present and future. IEEE Spectr. 34(6), 52–59 (1997) Robert, R.S.: Moore’s law: past, present and future. IEEE Spectr. 34(6), 52–59 (1997)
5.
Zurück zum Zitat Brian R.: The Origins of Digital Computers: Selected Papers. Springer (2013) Brian R.: The Origins of Digital Computers: Selected Papers. Springer (2013)
6.
Zurück zum Zitat Toumey, C.: Less is moore. Nature Nanotechnol. 11, 2–3 (2016) Toumey, C.: Less is moore. Nature Nanotechnol. 11, 2–3 (2016)
7.
Zurück zum Zitat Mead, C.: Neuromorphic electronic systems. Proc. IEEE 78(10), 1629–1636 (1990) Mead, C.: Neuromorphic electronic systems. Proc. IEEE 78(10), 1629–1636 (1990)
8.
Zurück zum Zitat Nikola, K., Neelava, S., Nathan, S.: From von neumann, John atanasoff and abc to neuromorphic computation and the neucube spatio-temporal data machine. In: 2016 IEEE 8th International Conference on Intelligent Systems (IS), pp. 15–21. IEEE (2016) Nikola, K., Neelava, S., Nathan, S.: From von neumann, John atanasoff and abc to neuromorphic computation and the neucube spatio-temporal data machine. In: 2016 IEEE 8th International Conference on Intelligent Systems (IS), pp. 15–21. IEEE (2016)
9.
Zurück zum Zitat Ivan, S.: Neuromorphic Computing: From Materials To Systems Architecture. Accessed 16 July 2016 Ivan, S.: Neuromorphic Computing: From Materials To Systems Architecture. Accessed 16 July 2016
10.
Zurück zum Zitat Calimera, A., Macii, E., Poncino, M.: The human brain project and neuromorphic computing. Function. Neurol. 28(3), 191–196 (2013) Calimera, A., Macii, E., Poncino, M.: The human brain project and neuromorphic computing. Function. Neurol. 28(3), 191–196 (2013)
11.
Zurück zum Zitat Hsu, J.: Ibm’s new brain [news]. IEEE Spectr. 51(10), 17–19 (2014) Hsu, J.: Ibm’s new brain [news]. IEEE Spectr. 51(10), 17–19 (2014)
12.
Zurück zum Zitat Merolla, P.A., Arthur, J.V., Rodrigo, A.-I., Cassidy, A.S., Sawada, J., Akopyan, F., Jackson, B.L., Imam, N., Guo, C., Nakamura, Y. et al.: A million spiking-neuron integrated circuit with a scalable communication network and interface. Science 345(6197), 668–673 (2014) Merolla, P.A., Arthur, J.V., Rodrigo, A.-I., Cassidy, A.S., Sawada, J., Akopyan, F., Jackson, B.L., Imam, N., Guo, C., Nakamura, Y. et al.: A million spiking-neuron integrated circuit with a scalable communication network and interface. Science 345(6197), 668–673 (2014)
13.
Zurück zum Zitat Ben, V.B., Peiran, G., McQuinn, E., Swadesh, C., Anand, R.C., Bussat, J.-M., Rodrigo, A.-I., John, V.A., Paul, A.M., Kwabena, B.N.: A mixed-analog-digital multichip system for large-scale neural simulations. Proc. IEEE 102(5), 699–716 (2014)CrossRef Ben, V.B., Peiran, G., McQuinn, E., Swadesh, C., Anand, R.C., Bussat, J.-M., Rodrigo, A.-I., John, V.A., Paul, A.M., Kwabena, B.N.: A mixed-analog-digital multichip system for large-scale neural simulations. Proc. IEEE 102(5), 699–716 (2014)CrossRef
14.
Zurück zum Zitat Steve, B., Furber, D., Lester, R., Luis, Plana, A., Jim, D., Garside, E.P., Steve, T., Andrew, D.B.: Overview of the spinnaker system architecture. IEEE Trans. Comput. 62(12), 2454–2467 (2013) Steve, B., Furber, D., Lester, R., Luis, Plana, A., Jim, D., Garside, E.P., Steve, T., Andrew, D.B.: Overview of the spinnaker system architecture. IEEE Trans. Comput. 62(12), 2454–2467 (2013)
15.
Zurück zum Zitat Indiveri, G., Linares-Barranco, Bernabé, H., Tara, J., Van Schaik, A., Etienne-Cummings, R., Delbruck, T., Liu, Shih-Chii, Dudek, Piotr, Häfliger, Philipp, Renaud, S., et al.: Neuromorphic silicon neuron circuits. Front. Neurosci. 5, 73 (2011) Indiveri, G., Linares-Barranco, Bernabé, H., Tara, J., Van Schaik, A., Etienne-Cummings, R., Delbruck, T., Liu, Shih-Chii, Dudek, Piotr, Häfliger, Philipp, Renaud, S., et al.: Neuromorphic silicon neuron circuits. Front. Neurosci. 5, 73 (2011)
16.
Zurück zum Zitat Indiveri, Giacomo: Liu, S.-C. Memory and information processing in neuromorphic systems. Proc. IEEE 103(8), 1379–1397 (2015)CrossRef Indiveri, Giacomo: Liu, S.-C. Memory and information processing in neuromorphic systems. Proc. IEEE 103(8), 1379–1397 (2015)CrossRef
17.
Zurück zum Zitat Maass, W.: Networks of spiking neurons: the third generation of neural network models. Neural Netw. 10(9), 1659–1671 (1997)CrossRef Maass, W.: Networks of spiking neurons: the third generation of neural network models. Neural Netw. 10(9), 1659–1671 (1997)CrossRef
18.
Zurück zum Zitat Maass, W., Bishop, C.M.: Pulsed Neural Networks. MIT press, New york (2001)MATH Maass, W., Bishop, C.M.: Pulsed Neural Networks. MIT press, New york (2001)MATH
19.
Zurück zum Zitat Elisa, C., Nikola, K., Grace, Y., Wang et al.: Analysis of connectivity in neucube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: a case study on opiate dependence treatment. Neural Netw. 68:62–77 (2015) Elisa, C., Nikola, K., Grace, Y., Wang et al.: Analysis of connectivity in neucube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: a case study on opiate dependence treatment. Neural Netw. 68:62–77 (2015)
20.
Zurück zum Zitat Maryam Gholami, D., Elisa, C., Nikola, K.: Classification and segmentation of fmri spatio-temporal brain data with a neucube evolving spiking neural network model. In: 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS), pp. 73–80. IEEE (2014) Maryam Gholami, D., Elisa, C., Nikola, K.: Classification and segmentation of fmri spatio-temporal brain data with a neucube evolving spiking neural network model. In: 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS), pp. 73–80. IEEE (2014)
21.
Zurück zum Zitat Delbruck, T., Patrick, L.: Fast sensory motor control based on event-based hybrid neuromorphic-procedural system. In: Circuits and Systems, 2007. ISCAS 2007. IEEE International Symposium on, pp. 845–848. IEEE (2007) Delbruck, T., Patrick, L.: Fast sensory motor control based on event-based hybrid neuromorphic-procedural system. In: Circuits and Systems, 2007. ISCAS 2007. IEEE International Symposium on, pp. 845–848. IEEE (2007)
22.
Zurück zum Zitat Nikola, K., Nathan, M.S., Enmei, T., Stefan, M., Neelava, S., Elisa, C., Muhaini, O., Maryam, G., Doborjeh, Norhanifah M., Reggio, H., et al.: Evolving spatio-temporal data machines based on the neucube neuromorphic framework design methodology and selected applications. Neural Netw. 78, 1–14 (2016) Nikola, K., Nathan, M.S., Enmei, T., Stefan, M., Neelava, S., Elisa, C., Muhaini, O., Maryam, G., Doborjeh, Norhanifah M., Reggio, H., et al.: Evolving spatio-temporal data machines based on the neucube neuromorphic framework design methodology and selected applications. Neural Netw. 78, 1–14 (2016)
24.
Zurück zum Zitat Sandberg, W.: Universal approximation using radial-basis-function networks. Neural Computat 3(2), 246–257 (1991) Sandberg, W.: Universal approximation using radial-basis-function networks. Neural Computat 3(2), 246–257 (1991)
25.
Zurück zum Zitat Donald, F.: Specht. Probabilistic neural networks. Neural networks 3(1), 109–118 (1990)CrossRef Donald, F.: Specht. Probabilistic neural networks. Neural networks 3(1), 109–118 (1990)CrossRef
26.
Zurück zum Zitat Kohonen, T.: The self-organizing map. Neurocomputing 21(1), 1–6 (1998) Kohonen, T.: The self-organizing map. Neurocomputing 21(1), 1–6 (1998)
27.
Zurück zum Zitat Nikola, K.: Evolving connectionist systems: the knowledge engineering approach. Springer Science & Business Media (2007) Nikola, K.: Evolving connectionist systems: the knowledge engineering approach. Springer Science & Business Media (2007)
29.
Zurück zum Zitat Schaul, Tom: Bayer, Justin, Wierstra, Daan, Sun, Yi, Felder, Martin, Sehnke, Frank, Rückstieß, Thomas, Schmidhuber, Jürgen: Pybrain. J. Mach. Learn. Res. 11, 743–746 (2010) Schaul, Tom: Bayer, Justin, Wierstra, Daan, Sun, Yi, Felder, Martin, Sehnke, Frank, Rückstieß, Thomas, Schmidhuber, Jürgen: Pybrain. J. Mach. Learn. Res. 11, 743–746 (2010)
30.
Zurück zum Zitat Steffen, N., Evan, N.: Fast artificial neural network library. leenissen.dk/fann/html/files/fann-h.html. (2000) Steffen, N., Evan, N.: Fast artificial neural network library. leenissen.dk/fann/html/files/fann-h.html. (2000)
31.
Zurück zum Zitat Mark, H., Eibe, F., Geoffrey, H., Bernhard, P., Peter, R., Ian, H.W.: The Weka data mining software: an update. ACM SIGKDD Explorat. Newslett. 11(1):10–18 (2009) Mark, H., Eibe, F., Geoffrey, H., Bernhard, P., Peter, R., Ian, H.W.: The Weka data mining software: an update. ACM SIGKDD Explorat. Newslett. 11(1):10–18 (2009)
32.
Zurück zum Zitat Michael, R.B., Nicolas, C., Fabian, D., Thomas, R., Gabriel, Tobias, K., Thorsten, M., Peter, O., Christoph, S., Kilian, T., Bernd, W.K.: The konstanz information miner. In: Data Analysis, Machine Learning and Applications, pp. 319–326. Springer (2008) Michael, R.B., Nicolas, C., Fabian, D., Thomas, R., Gabriel, Tobias, K., Thorsten, M., Peter, O., Christoph, S., Kilian, T., Bernd, W.K.: The konstanz information miner. In: Data Analysis, Machine Learning and Applications, pp. 319–326. Springer (2008)
33.
Zurück zum Zitat Demšar, J., Zupan, B., Leban, G., Tomaz, C.: From experimental machine learning to interactive data mining. Springer, Orange (2004) Demšar, J., Zupan, B., Leban, G., Tomaz, C.: From experimental machine learning to interactive data mining. Springer, Orange (2004)
34.
Zurück zum Zitat Michael, L., Hines, N., Carnevale, T.: The neuron simulation environment. Neural Comput. 9(6), 1179–1209 (1997) Michael, L., Hines, N., Carnevale, T.: The neuron simulation environment. Neural Comput. 9(6), 1179–1209 (1997)
35.
Zurück zum Zitat Romain, B., Michelle, R., Ted, C., Hines, M., Beeman, D., Bower, J.M., Diesmann, M., Morrison, A., Goodman, P.H., Harris, Jr., Frederick, C., et al.: Simulation of networks of spiking neurons: a review of tools and strategies. J. Comput. Neurosci. 23(3), 349–398 (2007) Romain, B., Michelle, R., Ted, C., Hines, M., Beeman, D., Bower, J.M., Diesmann, M., Morrison, A., Goodman, P.H., Harris, Jr., Frederick, C., et al.: Simulation of networks of spiking neurons: a review of tools and strategies. J. Comput. Neurosci. 23(3), 349–398 (2007)
36.
Zurück zum Zitat Jochen Martin, E., Moritz, H., Eilif, M., Markus, D., Marc-Oliver, G.: Pynest: a convenient interface to the nest simulator. Front. Neuroinformat. 2 (2008) Jochen Martin, E., Moritz, H., Eilif, M., Markus, D., Marc-Oliver, G.: Pynest: a convenient interface to the nest simulator. Front. Neuroinformat. 2 (2008)
37.
Zurück zum Zitat Dejan, P., Thomas, N.,Klaus, S.: Pcsim: a parallel simulation environment for neural circuits fully integrated with python. Front. Neuroinformat. 3 (2009) Dejan, P., Thomas, N.,Klaus, S.: Pcsim: a parallel simulation environment for neural circuits fully integrated with python. Front. Neuroinformat. 3 (2009)
38.
Zurück zum Zitat Thomas, N., Henry, M., Wolfgang, M.: Computer models and analysis tools for neural microcircuits. In: Neuroscience Databases, pp. 123–138. Springer (2003) Thomas, N., Henry, M., Wolfgang, M.: Computer models and analysis tools for neural microcircuits. In: Neuroscience Databases, pp. 123–138. Springer (2003)
39.
Zurück zum Zitat Rich, D.: Brainlab: a toolkit to aid in the design, simulation, and analysis of spiking neural networks with the NCS environment. PhD thesis, University of Nevada Reno (2005) Rich, D.: Brainlab: a toolkit to aid in the design, simulation, and analysis of spiking neural networks with the NCS environment. PhD thesis, University of Nevada Reno (2005)
40.
Zurück zum Zitat E Courtenay, W.: Parallel implementation of a large scale biologically realistic neocortical neural network simulator. PhD thesis, University of Nevada Reno (2001) E Courtenay, W.: Parallel implementation of a large scale biologically realistic neocortical neural network simulator. PhD thesis, University of Nevada Reno (2001)
41.
Zurück zum Zitat Dejan, P.: Oger: Modular learning architectures for large-scale sequential processing Dejan, P.: Oger: Modular learning architectures for large-scale sequential processing
42.
Zurück zum Zitat Goodman, Dan, F.M.: Code generation: a strategy for neural network simulators. Neuroinformatics 8(3), 183–196 (2010) Goodman, Dan, F.M.: Code generation: a strategy for neural network simulators. Neuroinformatics 8(3), 183–196 (2010)
43.
Zurück zum Zitat Goodman, Dan, F.M., Brette, R.: The brian simulator. Front. Neurosci. 3(2), 192 (2009) Goodman, Dan, F.M., Brette, R.: The brian simulator. Front. Neurosci. 3(2), 192 (2009)
44.
Zurück zum Zitat Diesmann, M.: Gewaltig, Marc-Oliver, Aertsen, Ad: Stable propagation of synchronous spiking in cortical neural networks. Nature 402(6761), 529–533 (1999) Diesmann, M.: Gewaltig, Marc-Oliver, Aertsen, Ad: Stable propagation of synchronous spiking in cortical neural networks. Nature 402(6761), 529–533 (1999)
45.
Zurück zum Zitat Nikola, K.: Kasabov. Neucube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data. Neural Netw. 52, 62–76 (2014)CrossRef Nikola, K.: Kasabov. Neucube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data. Neural Netw. 52, 62–76 (2014)CrossRef
46.
Zurück zum Zitat Neelava Sengupta, Nathan Scott, Nikola, K.: Framework for knowledge driven optimisation based data encoding for brain data modelling using spiking neural network architecture. In: Proceedings of the Fifth International Conference on Fuzzy and Neuro Computing (FANCCO-2015), pp. 109–118. Springer (2015) Neelava Sengupta, Nathan Scott, Nikola, K.: Framework for knowledge driven optimisation based data encoding for brain data modelling using spiking neural network architecture. In: Proceedings of the Fifth International Conference on Fuzzy and Neuro Computing (FANCCO-2015), pp. 109–118. Springer (2015)
47.
Zurück zum Zitat Fusi, S.: Spike-driven synaptic plasticity for learning correlated patterns of mean firing rates. Rev. Neurosci. 14(1–2), 73–84 (2003) Fusi, S.: Spike-driven synaptic plasticity for learning correlated patterns of mean firing rates. Rev. Neurosci. 14(1–2), 73–84 (2003)
48.
Zurück zum Zitat Song, Sen: Kenneth D Miller, and Larry F Abbott. Competitive hebbian learning through spike-timing-dependent synaptic plasticity. Nature Neurosci. 3(9), 919–926 (2000) Song, Sen: Kenneth D Miller, and Larry F Abbott. Competitive hebbian learning through spike-timing-dependent synaptic plasticity. Nature Neurosci. 3(9), 919–926 (2000)
49.
Zurück zum Zitat Kasabov, N.: Dhoble, K., Nuntalid, N., Indiveri, G.: Dynamic evolving spiking neural networks for on-line spatio-and spectro-temporal pattern recognition. Neural NetW. 41, 188–201 (2013) Kasabov, N.: Dhoble, K., Nuntalid, N., Indiveri, G.: Dynamic evolving spiking neural networks for on-line spatio-and spectro-temporal pattern recognition. Neural NetW. 41, 188–201 (2013)
50.
Zurück zum Zitat Mohemmed, Ammar: Schliebs, Stefan, Matsuda, Satoshi, Kasabov, Nikola: Span: Spike pattern association neuron for learning spatio-temporal spike patterns. Int. J. Neural Syst. 22(04), 1250012 (2012)CrossRef Mohemmed, Ammar: Schliebs, Stefan, Matsuda, Satoshi, Kasabov, Nikola: Span: Spike pattern association neuron for learning spatio-temporal spike patterns. Int. J. Neural Syst. 22(04), 1250012 (2012)CrossRef
51.
Zurück zum Zitat Nathan S., Nikola K., Giacomo Indiveri.: Neucube neuromorphic framework for spatio-temporal brain data and its python implementation. In: Neural Information Processing, pp. 78–84. Springer (2013) Nathan S., Nikola K., Giacomo Indiveri.: Neucube neuromorphic framework for spatio-temporal brain data and its python implementation. In: Neural Information Processing, pp. 78–84. Springer (2013)
52.
Zurück zum Zitat Marks, S., Javier, E., Nathan, S.: Immersive Visualisation Of 3-dimensional Neural Network Structures. (2015) Marks, S., Javier, E., Nathan, S.: Immersive Visualisation Of 3-dimensional Neural Network Structures. (2015)
53.
Zurück zum Zitat Stefan Marks. Immersive Visualisation Of 3-dimensional Spiking Neural Networks. Evolving Syst. pp. 1–9 (2016) Stefan Marks. Immersive Visualisation Of 3-dimensional Spiking Neural Networks. Evolving Syst. pp. 1–9 (2016)
54.
Zurück zum Zitat Kasabov, N., Yingjie, H.: Integrated optimisation method for personalised modelling and case studies for medical decision support. Int. J. Function. Informat. Personal. Med. 3(3), 236–256 (2010) Kasabov, N., Yingjie, H.: Integrated optimisation method for personalised modelling and case studies for medical decision support. Int. J. Function. Informat. Personal. Med. 3(3), 236–256 (2010)
55.
Zurück zum Zitat Maryam Gholami, D., Nikola, K.: Personalised modelling on integrated clinical and EEG spatio-temporal brain data in the neucube spiking neural network system. In: 2016 International Joint Conference on Neural Networks (IJCNN), pp. 1373–1378. IEEE (2016) Maryam Gholami, D., Nikola, K.: Personalised modelling on integrated clinical and EEG spatio-temporal brain data in the neucube spiking neural network system. In: 2016 International Joint Conference on Neural Networks (IJCNN), pp. 1373–1378. IEEE (2016)
56.
Zurück zum Zitat Hadi, E., Emily, B., Renee, S.T., Amant, K.S, Doug, B.: Dark silicon and the end of multicore scaling. ACM SIGARCH Comput. Architect. News 39(3):365 (2011) Hadi, E., Emily, B., Renee, S.T., Amant, K.S, Doug, B.: Dark silicon and the end of multicore scaling. ACM SIGARCH Comput. Architect. News 39(3):365 (2011)
57.
Zurück zum Zitat Perrin, D.: Complexity and high-end computing in biology and medicine. Advanc. Experiment. Med. Biol. 696, 377–84 (2011) Perrin, D.: Complexity and high-end computing in biology and medicine. Advanc. Experiment. Med. Biol. 696, 377–84 (2011)
58.
Zurück zum Zitat Furber, S.: To build a brain. IEEE Spect. 49(8), 44–49 (2012) Furber, S.: To build a brain. IEEE Spect. 49(8), 44–49 (2012)
59.
Zurück zum Zitat Indiveri, G., Linares-Barranco, Bernabé, Tara Julia, H., André van Schaik, Ralph Etienne-Cummings, Tobi Delbruck, Shih-Chii Liu, Piotr Dudek, Philipp, Häfliger, Sylvie, R., Johannes, S., Gert, C., John, A., Kai, H., Fopefolu, F., Sylvain, S., Teresa, S.-G., Jayawan, W., Yingxue, W., Kwabena, B.: Neuromorphic silicon neuron circuits. Front. Neurosci. 5, 73 (2011) Indiveri, G., Linares-Barranco, Bernabé, Tara Julia, H., André van Schaik, Ralph Etienne-Cummings, Tobi Delbruck, Shih-Chii Liu, Piotr Dudek, Philipp, Häfliger, Sylvie, R., Johannes, S., Gert, C., John, A., Kai, H., Fopefolu, F., Sylvain, S., Teresa, S.-G., Jayawan, W., Yingxue, W., Kwabena, B.: Neuromorphic silicon neuron circuits. Front. Neurosci. 5, 73 (2011)
60.
Zurück zum Zitat Andrew, P., Davison, D., Brüderle, Jochen, E., Jens, K., Eilif, M., Dejan, P., Laurent, P., Pierre, Y.: PyNN: A common interface for neuronal network simulators. Front. Neuroinformat. 211 (2008) Andrew, P., Davison, D., Brüderle, Jochen, E., Jens, K., Eilif, M., Dejan, P., Laurent, P., Pierre, Y.: PyNN: A common interface for neuronal network simulators. Front. Neuroinformat. 211 (2008)
61.
Zurück zum Zitat Bruckner, S., Solteszova, V., Groller, E., Hladuvka, J., Buhler, K., Yu, J., Dickson, B.: BrainGazer–visual queries for neurobiology research. IEEE Trans. Visualizat. Comput. Graph. 15(6), 1497–1504 (2009)CrossRef Bruckner, S., Solteszova, V., Groller, E., Hladuvka, J., Buhler, K., Yu, J., Dickson, B.: BrainGazer–visual queries for neurobiology research. IEEE Trans. Visualizat. Comput. Graph. 15(6), 1497–1504 (2009)CrossRef
62.
Zurück zum Zitat Lin, C.-Y. Tsai, ,K.-L., Wang, S.-C., Hsieh, C.-H., Chang, H.-M., Chiang, A.-S.: The neuron navigator: exploring the information pathway through the neural maze. In: IEEE Pacific Visualization Symposium (PacificVis) 20, pp. 35–42 (2011) Lin, C.-Y. Tsai, ,K.-L., Wang, S.-C., Hsieh, C.-H., Chang, H.-M., Chiang, A.-S.: The neuron navigator: exploring the information pathway through the neural maze. In: IEEE Pacific Visualization Symposium (PacificVis) 20, pp. 35–42 (2011)
63.
Zurück zum Zitat von Kapri, A., Rick, T., Potjans, T.C., Diesmann, M., Kuhlen, T.: Towards the visualization of spiking neurons in virtual reality. Stud. Health Technol. Informat. 163, 685–87 (2011) von Kapri, A., Rick, T., Potjans, T.C., Diesmann, M., Kuhlen, T.: Towards the visualization of spiking neurons in virtual reality. Stud. Health Technol. Informat. 163, 685–87 (2011)
Metadaten
Titel
From von Neumann Architecture and Atanasoffs ABC to Neuro-Morphic Computation and Kasabov’s NeuCube: Principles and Implementations
verfasst von
Neelava Sengupta
Josafath Israel Espinosa Ramos
Enmei Tu
Stefan Marks
Nathan Scott
Jakub Weclawski
Akshay Raj Gollahalli
Maryam Gholami Doborjeh
Zohreh Gholami Doborjeh
Kaushalya Kumarasinghe
Vivienne Breen
Anne Abbott
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-75181-8_1