Academic literature on the topic 'Dynamical memory'
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Journal articles on the topic "Dynamical memory"
Ganguli, S., D. Huh, and H. Sompolinsky. "Memory traces in dynamical systems." Proceedings of the National Academy of Sciences 105, no. 48 (November 19, 2008): 18970–75. http://dx.doi.org/10.1073/pnas.0804451105.
Full textRehn, Martin, and Anders Lansner. "Sequence memory with dynamical synapses." Neurocomputing 58-60 (June 2004): 271–78. http://dx.doi.org/10.1016/j.neucom.2004.01.055.
Full textMitchell, Melanie. "Human Memory: A Dynamical Process." Contemporary Psychology 48, no. 3 (June 2003): 326–27. http://dx.doi.org/10.1037/000805.
Full textBoffetta, G., R. Monasson, and R. Zecchina. "MEMORY RETRIEVAL IN OPTIMAL SUBSPACES." International Journal of Neural Systems 03, supp01 (January 1992): 71–77. http://dx.doi.org/10.1142/s0129065792000401.
Full textAICARDI, FRANCESCA, and SERGIO INVERNIZZI. "MEMORY EFFECTS IN DISCRETE DYNAMICAL SYSTEMS." International Journal of Bifurcation and Chaos 02, no. 04 (December 1992): 815–30. http://dx.doi.org/10.1142/s0218127492000458.
Full textKlinshov, Vladimir V., and Vladimir I. Nekorkin. "Dynamical model of working memory system." Neuroscience Research 58 (January 2007): S44. http://dx.doi.org/10.1016/j.neures.2007.06.259.
Full textBrianzoni, Serena, Cristiana Mammana, Elisabetta Michetti, and Francesco Zirilli. "A Stochastic Cobweb Dynamical Model." Discrete Dynamics in Nature and Society 2008 (2008): 1–18. http://dx.doi.org/10.1155/2008/219653.
Full textOliveira, H. S., A. S. de Paula, and M. A. Savi. "Dynamical Jumps in a Shape Memory Alloy Oscillator." Shock and Vibration 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/656212.
Full textMohapatra, Anushaya, and William Ott. "Memory loss for nonequilibrium open dynamical systems." Discrete & Continuous Dynamical Systems - A 34, no. 9 (2014): 3747–59. http://dx.doi.org/10.3934/dcds.2014.34.3747.
Full textOtt, William, Mikko Stenlund, and Lai-Sang Young. "Memory loss for time-dependent dynamical systems." Mathematical Research Letters 16, no. 3 (2009): 463–75. http://dx.doi.org/10.4310/mrl.2009.v16.n3.a7.
Full textDissertations / Theses on the topic "Dynamical memory"
Liu, Yuxi. "Dynamical Activity Patterns of High-frequency Oscillations and Their Functional Roles in Neural Circuits." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/23236.
Full textKropff, Emilio. "Statistical and dynamical properties of large cortical network models: insights into semantic memory and language." Doctoral thesis, SISSA, 2007. http://hdl.handle.net/20.500.11767/4639.
Full textRehn, Martin. "Aspects of memory and representation in cortical computation." Doctoral thesis, KTH, Numerisk Analys och Datalogi, NADA, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4161.
Full textIn this thesis I take a modular approach to cortical function. I investigate how the cerebral cortex may realise a number of basic computational tasks, within the framework of its generic architecture. I present novel mechanisms for certain assumed computational capabilities of the cerebral cortex, building on the established notions of attractor memory and sparse coding. A sparse binary coding network for generating efficient representations of sensory input is presented. It is demonstrated that this network model well reproduces the simple cell receptive field shapes seen in the primary visual cortex and that its representations are efficient with respect to storage in associative memory. I show how an autoassociative memory, augmented with dynamical synapses, can function as a general sequence learning network. I demonstrate how an abstract attractor memory system may be realised on the microcircuit level -- and how it may be analysed using tools similar to those used experimentally. I outline some predictions from the hypothesis that the macroscopic connectivity of the cortex is optimised for attractor memory function. I also discuss methodological aspects of modelling in computational neuroscience.
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Bhalala, Smita Ashesh 1966. "Modified Newton's method for supervised training of dynamical neural networks for applications in associative memory and nonlinear identification problems." Thesis, The University of Arizona, 1991. http://hdl.handle.net/10150/277969.
Full textBauer, Michael. "Dynamical characterization of Markov processes with varying order." Master's thesis, [S.l. : s.n.], 2009. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200900153.
Full textAbbs, Brandon Robert. "The temporal dynamics of auditory memory for static and dynamic sounds." Diss., University of Iowa, 2008. http://ir.uiowa.edu/etd/4.
Full textWilliams, Peter. "Dynamic memory for design." Thesis, The University of Sydney, 1995. https://hdl.handle.net/2123/27472.
Full textSperens, Martin. "Dynamic Memory Managment in C++." Thesis, Luleå tekniska universitet, Datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-76611.
Full textBisht, Pawas. "Disaster and the dynamics of memory." Thesis, Loughborough University, 2013. https://dspace.lboro.ac.uk/2134/14184.
Full textWu, Jiaming. "A modular dynamic Neuro-Synaptic platform for Spiking Neural Networks." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASP145.
Full textBiological and artificial neural networks share a fundamental computational unit: the neuron. These neurons are coupled by synapses, forming complex networks that enable various functions. Similarly, neuromorphic hardware, or more generally neuro-computers, also require two hardware elements: neurons and synapses. In this work, we introduce a bio-inspired spiking Neuro-Synaptic hardware unit, fully implemented with conventional electronic components. Our hardware is based on a textbook theoretical model of the spiking neuron, and its synaptic and membrane currents. The spiking neuron is fully analog and the various models that we introduced are defined by their hardware implementation. The neuron excitability is achieved through a memristive device made from off-the-shelf electronic components. Both synaptic and membrane currents feature tunable intensities and bio-mimetic dynamics, including excitatory and inhibitory currents. All model parameters are adjustable, allowing the system to be tuned to bio-compatible timescales, which is crucial in applications such as brain-machine interfaces. Building on these two modular units, we demonstrate various basic neural network motifs (or neuro-computing primitives) and show how to combine these fundamental motifs to implement more complex network functionalities, such as dynamical memories and central pattern generators. Our hardware design also carries potential extensions for integrating oxide-based memristors (which are widely studied in material science),or porting the design to very large-scale integration (VLSI) to implement large-scale networks. The Neuro-Synaptic unit can be considered as a building block for implementing spiking neural networks of arbitrary geometry. Its compact and modular design, as well as the wide availability of ordinary electronic components, makes our approach an attractive platform for building neural interfaces in medical devices, robotics, and artificial intelligence systems such as reservoir computing
Books on the topic "Dynamical memory"
Irene, Dorfman, Fokas A. S. 1952-, and Gelʹfand I. M, eds. Algebraic aspects of integrable systems: In memory of Irene Dorfman. Boston: Birkäuser, 1997.
Find full textBlokh, Alexander, Leonid Bunimovich, Paul Jung, Lex Oversteegen, and Yakov Sinai, eds. Dynamical Systems, Ergodic Theory, and Probability: in Memory of Kolya Chernov. Providence, Rhode Island: American Mathematical Society, 2017. http://dx.doi.org/10.1090/conm/698.
Full textV, Anosov D., Stepin A. M, and Bolibruch Andrej Andreevič, eds. Dynamical systems and related problems of geometry: Collected papers dedicated to the memory of academician Andrei Andreevich Bolibrukh. Moscow: Maik Nauka/Interperiodica, 2004.
Find full textMotorola. Dynamic RAMs & memory modules. 2nd ed. Phoenix, AZ: Motorola, 1996.
Find full textKorostelina, Karina V. Memory Sites and Conflict Dynamics. London: Routledge, 2024. http://dx.doi.org/10.4324/9781003497332.
Full textMotorola. Dynamic RAMs and memory modules. Phoenix, AZ: Motorola, 1993.
Find full textAtienza Alonso, David, Stylianos Mamagkakis, Christophe Poucet, Miguel Peón-Quirós, Alexandros Bartzas, Francky Catthoor, and Dimitrios Soudris. Dynamic Memory Management for Embedded Systems. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-10572-7.
Full textIncorporated, Advanced Micro Devices. Dynamic memory design data book/handbook. [Sunnyvale, CA]: Advanced Micro Devices, Inc., 1990.
Find full textDaconta, Michael C. C++ pointers and dynamic memory management. New York: Wiley, 1995.
Find full textFarkas, Keith I. Memory-system design considerations for dynamically-scheduled microprocessors. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1997.
Find full textBook chapters on the topic "Dynamical memory"
Pandolfi, Luciano. "Dynamical Algorithms for Identification Problems." In Systems with Persistent Memory, 283–329. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80281-3_6.
Full textLiu, Jun, and Andrew R. Teel. "Hybrid Dynamical Systems with Finite Memory." In Recent Results on Nonlinear Delay Control Systems, 261–73. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18072-4_13.
Full textFung, C. C. Alan, K. Y. Michael Wong, and Si Wu. "Dynamical Synapses Enhance Mobility, Memory and Decoding." In Advances in Cognitive Neurodynamics (III), 131–37. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-4792-0_18.
Full textCosnard, Michel, and Eric Goles Chacc. "Dynamical Properties of An Automaton with Memory." In Disordered Systems and Biological Organization, 63–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-82657-3_7.
Full textBragov, A. M., L. A. Igumnov, A. Yu Konstantinov, A. K. Lomunov, and A. I. Razov. "Dynamic Research of Shape Memory Alloys." In Dynamical Processes in Generalized Continua and Structures, 133–46. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11665-1_7.
Full textGrasselli, Maurizio, and Vittorino Pata. "Uniform Attractors of Nonautonomous Dynamical Systems with Memory." In Evolution Equations, Semigroups and Functional Analysis, 155–78. Basel: Birkhäuser Basel, 2002. http://dx.doi.org/10.1007/978-3-0348-8221-7_9.
Full textButaud, Pauline, Morvan Ouisse, Kévin Jaboviste, Vincent Placet, and Emmanuel Foltête. "Dynamical Mechanical Thermal Analysis of Shape-Memory Polymers." In Advanced Structured Materials, 129–51. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8574-2_6.
Full textSoares, O. D. D., A. L. V. S. Lage, A. O. S. Gomes, and J. C. D. M. Santos. "Dynamical Digital Memory for Holography, Moiré and E.S.P.I." In Optical Metrology, 182–98. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3609-6_16.
Full textKoopmans, Matthijs. "Investigating the Long Memory Process in Daily High School Attendance Data." In Complex Dynamical Systems in Education, 299–321. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27577-2_14.
Full textHayashi, Hatsuo, and Motoharu Yoshida. "A Memory Model Based on Dynamical Behavior of the Hippocampus." In Lecture Notes in Computer Science, 967–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30132-5_130.
Full textConference papers on the topic "Dynamical memory"
Shen, Minghao, and Gábor Orosz. "Memory Sketching for Data-driven Prediction of Dynamical Systems." In 2024 American Control Conference (ACC), 5388–93. IEEE, 2024. http://dx.doi.org/10.23919/acc60939.2024.10645035.
Full textLoveridge, Tegan, Kai Shinbrough, and Virginia O. Lorenz. "Optimal Continuous Dynamical Decoupling in N-type Atomic Ensemble Quantum Memories." In CLEO: Fundamental Science, FM3R.4. Washington, D.C.: Optica Publishing Group, 2024. http://dx.doi.org/10.1364/cleo_fs.2024.fm3r.4.
Full textOtsuka, Kenju, and Jyh-Long Chern. "Factorial Dynamic Pattern Memory in Globally Coupled Lasers." In Nonlinear Dynamics in Optical Systems. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/nldos.1992.thb1.
Full textGordon, Goren, and Gershon Kurizki. "Dynamical control of noisy quantum memory channels." In Microtechnologies for the New Millennium, edited by Ali Serpengüzel, Gonçal Badenes, and Giancarlo C. Righini. SPIE, 2007. http://dx.doi.org/10.1117/12.723952.
Full textDuda, Alexander M., and Stephen E. Levinson. "Nonlinear Dynamical Multi-Scale Model of Associative Memory." In 2010 International Conference on Machine Learning and Applications (ICMLA). IEEE, 2010. http://dx.doi.org/10.1109/icmla.2010.135.
Full textChung-Ming Ou and C. R. Ou. "Immune memory with associativity: Perspectives on dynamical systems." In 2012 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2012. http://dx.doi.org/10.1109/cec.2012.6256646.
Full textAndrianov, Serge N., and Nikolai S. Edamenko. "Geometric integration of nonlinear dynamical systems." In 2015 International Conference "Stability and Control Processes" in Memory of V.I. Zubov (SCP). IEEE, 2015. http://dx.doi.org/10.1109/scp.2015.7342048.
Full textVakhnenko, Vyacheslav O. "Dynamical realization of end-point memory in consolidated materials." In INNOVATIONS IN NONLINEAR ACOUSTICS: ISNA17 - 17th International Symposium on Nonlinear Acoustics including the International Sonic Boom Forum. AIP, 2006. http://dx.doi.org/10.1063/1.2210332.
Full textAlonso-Sanz, Ramon. "Cellular automata and other discrete dynamical systems with memory." In 2012 International Conference on High Performance Computing & Simulation (HPCS). IEEE, 2012. http://dx.doi.org/10.1109/hpcsim.2012.6266914.
Full textDavydenko, Alexander A., Natalya V. Raspopova, and Sergei S. Ustimenko. "On mass simulations of dynamical models of galaxy." In 2015 International Conference "Stability and Control Processes" in Memory of V.I. Zubov (SCP). IEEE, 2015. http://dx.doi.org/10.1109/scp.2015.7342053.
Full textReports on the topic "Dynamical memory"
Beri, A. C., and T. F. George. Memory Effects in Dynamical Many-Body Systems: The Isomnesic (Constant-Memory) Approximation. Fort Belvoir, VA: Defense Technical Information Center, April 1985. http://dx.doi.org/10.21236/ada154160.
Full textPerdigão, Rui A. P., and Julia Hall. Spatiotemporal Causality and Predictability Beyond Recurrence Collapse in Complex Coevolutionary Systems. Meteoceanics, November 2020. http://dx.doi.org/10.46337/201111.
Full textAsea, Patrick K., and Michael J. Dueker. Non-Monotonic Long Memory Dynamics in Black-Market Exchange Rates. Federal Reserve Bank of St. Louis, 1995. http://dx.doi.org/10.20955/wp.1995.003.
Full textKim, Joohee, and Marios C. Papaefthymiou. Block-Based Multi-Period Refresh for Energy Efficient Dynamic Memory. Fort Belvoir, VA: Defense Technical Information Center, April 2002. http://dx.doi.org/10.21236/ada414244.
Full textLagoudas, Dimitris C. Dynamic Behavior and Shock Absorption Properties of Porous Shape Memory Alloys. Fort Belvoir, VA: Defense Technical Information Center, July 2002. http://dx.doi.org/10.21236/ada403775.
Full textSaxena, A., A. R. Bishop, S. R. Shenoy, Y. Wu, and T. Lookman. A model of shape memory materials with hierarchical twinning: Statics and dynamics. Office of Scientific and Technical Information (OSTI), July 1995. http://dx.doi.org/10.2172/102295.
Full textMayas, Magda. Creating with timbre. Norges Musikkhøgskole, August 2018. http://dx.doi.org/10.22501/nmh-ar.686088.
Full textD`Azevedo, E. F., and C. H. Romine. A new shared-memory programming paradigm for molecular dynamics simulations on the Intel Paragon. Office of Scientific and Technical Information (OSTI), December 1994. http://dx.doi.org/10.2172/28414.
Full textD'Azevedo, E. F. A New Shared-Memory Programming Paradigm for Molecular Dynamics Simulations on the Intel Paragon. Office of Scientific and Technical Information (OSTI), January 1995. http://dx.doi.org/10.2172/814063.
Full textVineyard, Craig Michael, and Stephen Joseph Verzi. A Case Study on Neural Inspired Dynamic Memory Management Strategies for High Performance Computing. Office of Scientific and Technical Information (OSTI), September 2017. http://dx.doi.org/10.2172/1396076.
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