Measuring information transfer in a soft robotic arm
暂无分享,去创建一个
[1] L M Hively,et al. Detecting dynamical changes in time series using the permutation entropy. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[2] K. Keller,et al. Permutation entropy: One concept, two approaches , 2013 .
[3] C. Laschi,et al. Octopus-inspired sensorimotor control of a multi-arm soft robot , 2012, 2012 IEEE International Conference on Mechatronics and Automation.
[4] Karsten Keller,et al. On the relation of KS entropy and permutation entropy , 2012, 1407.6473.
[5] H Kantz,et al. Direction of coupling from phases of interacting oscillators: a permutation information approach. , 2008, Physical review letters.
[6] Dimitris Kugiumtzis,et al. Transfer Entropy on Rank Vectors , 2010, ArXiv.
[7] Dario Paolo,et al. Design Of A Biomimetic Robotic Octopus Arm , 2008 .
[8] B Mazzolai,et al. An octopus-bioinspired solution to movement and manipulation for soft robots , 2011, Bioinspiration & biomimetics.
[9] Helmut Hauser,et al. A soft body as a reservoir: case studies in a dynamic model of octopus-inspired soft robotic arm , 2013, Front. Comput. Neurosci..
[10] Filip Ilievski,et al. Multigait soft robot , 2011, Proceedings of the National Academy of Sciences.
[11] G. Keller,et al. Entropy of interval maps via permutations , 2002 .
[12] Josh Bongard,et al. Morphological change in machines accelerates the evolution of robust behavior , 2011, Proceedings of the National Academy of Sciences.
[13] B. Hochner,et al. Control of Octopus Arm Extension by a Peripheral Motor Program , 2001, Science.
[14] K. Keller,et al. A standardized approach to the Kolmogorov-Sinai entropy , 2009 .
[15] Fumiya Iida,et al. The challenges ahead for bio-inspired 'soft' robotics , 2012, CACM.
[16] H. Kantz,et al. Analysing the information flow between financial time series , 2002 .
[17] Tao Li,et al. Behavior switching using reservoir computing for a soft robotic arm , 2012, 2012 IEEE International Conference on Robotics and Automation.
[18] Tao Li,et al. Local information transfer in soft robotic arm , 2012, 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO).
[19] Jürgen Kurths,et al. Escaping the curse of dimensionality in estimating multivariate transfer entropy. , 2012, Physical review letters.
[20] Kohei Nakajima,et al. Permutation Complexity and Coupling Measures in Hidden Markov Models , 2012, Entropy.
[21] B. Hochner. An Embodied View of Octopus Neurobiology , 2012, Current Biology.
[22] Kohei Nakajima,et al. Permutation approach to finite-alphabet stationary stochastic processes based on the duality between values and orderings , 2013 .
[23] Rolf Pfeifer,et al. How the body shapes the way we think - a new view on intelligence , 2006 .
[24] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[25] Kohei Nakajima,et al. Symbolic transfer entropy rate is equal to transfer entropy rate for bivariate finite-alphabet stationary ergodic Markov processes , 2011, 1112.2493.
[26] Schreiber,et al. Measuring information transfer , 2000, Physical review letters.
[27] B. Pompe,et al. Permutation entropy: a natural complexity measure for time series. , 2002, Physical review letters.
[28] Jürgen Kurths,et al. Quantifying Causal Coupling Strength: A Lag-specific Measure For Multivariate Time Series Related To Transfer Entropy , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.
[29] Cecilia Laschi,et al. Soft robotics: a bioinspired evolution in robotics. , 2013, Trends in biotechnology.
[30] Karsten Keller,et al. An approach to comparing Kolmogorov-Sinai and permutation entropy , 2013 .
[31] B Mazzolai,et al. Design of a biomimetic robotic octopus arm , 2009, Bioinspiration & biomimetics.
[32] Ian D. Walker,et al. Soft robotics: Biological inspiration, state of the art, and future research , 2008 .
[33] Dimitris Kugiumtzis,et al. Partial transfer entropy on rank vectors , 2013, ArXiv.
[34] Germán Sumbre,et al. Neurobiology: Motor control of flexible octopus arms , 2005, Nature.
[35] Darwin G. Caldwell,et al. Timing-based control via echo state network for soft robotic arm , 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).
[36] Kohei Nakajima,et al. Symbolic local information transfer , 2013, The European Physical Journal Special Topics.
[37] Paolo Dario,et al. Soft Robot Arm Inspired by the Octopus , 2012, Adv. Robotics.
[38] Helmut Hauser,et al. Computing with a muscular-hydrostat system , 2013, 2013 IEEE International Conference on Robotics and Automation.
[39] Rolf Pfeifer,et al. Bootstrapping Perception using Information Theory: Case Studies in a quadruped Robot Running on Different grounds , 2013, Adv. Complex Syst..
[40] Olaf Sporns,et al. Mapping Information Flow in Sensorimotor Networks , 2006, PLoS Comput. Biol..
[41] Tao Li,et al. Online learning for behavior switching in a soft robotic arm , 2013, 2013 IEEE International Conference on Robotics and Automation.
[42] Karsten Keller,et al. Permutations and the Kolmogorov-Sinai entropy , 2011 .
[43] Kohei Nakajima,et al. FROM THE OCTOPUS TO SOFT ROBOTS CONTROL: AN OCTOPUS INSPIRED BEHAVIOR CONTROL ARCHITECTURE FOR SOFT ROBOTS , 2012 .
[44] R. Pfeifer,et al. Self-Organization, Embodiment, and Biologically Inspired Robotics , 2007, Science.
[45] Tao Li,et al. Information theoretic analysis on a soft robotic arm inspired by the octopus , 2011, 2011 IEEE International Conference on Robotics and Biomimetics.
[46] José M. Amigó,et al. The equality of Kolmogorov–Sinai entropy and metric permutation entropy generalized , 2012 .
[47] P. Dario,et al. Design concept and validation of a robotic arm inspired by the octopus , 2011 .
[48] O A Rosso,et al. Distinguishing noise from chaos. , 2007, Physical review letters.
[49] Ralf Der,et al. Information Driven Self-Organization of Complex Robotic Behaviors , 2013, PloS one.
[50] Matthäus Staniek,et al. Symbolic transfer entropy. , 2008, Physical review letters.
[51] Daniel Polani,et al. Information Flows in Causal Networks , 2008, Adv. Complex Syst..
[52] Mikhail Prokopenko,et al. Differentiating information transfer and causal effect , 2008, 0812.4373.
[53] L. Kocarev,et al. The permutation entropy rate equals the metric entropy rate for ergodic information sources and ergodic dynamical systems , 2005, nlin/0503044.
[54] B. Pompe,et al. Momentary information transfer as a coupling measure of time series. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.
[55] Mathieu Sinn,et al. Kolmogorov-Sinai entropy from the ordinal viewpoint , 2010 .
[56] Kohei Nakajima,et al. Permutation Complexity via Duality between Values and Orderings , 2011, ArXiv.
[57] Aubery Marchel Tientcheu Ngouabeu,et al. Morphology-Induced Collective Behaviors: Dynamic Pattern Formation in Water-Floating Elements , 2012, PloS one.
[58] Viola Priesemann,et al. Measuring Information-Transfer Delays , 2013, PloS one.
[59] Albert Y. Zomaya,et al. Local information transfer as a spatiotemporal filter for complex systems. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[60] José Amigó,et al. Permutation Complexity in Dynamical Systems , 2010 .
[61] Olivier J. J. Michel,et al. On directed information theory and Granger causality graphs , 2010, Journal of Computational Neuroscience.