Literatura científica selecionada sobre o tema "Dynamical memory"
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Artigos de revistas sobre o assunto "Dynamical memory"
Ganguli, S., D. Huh e H. Sompolinsky. "Memory traces in dynamical systems". Proceedings of the National Academy of Sciences 105, n.º 48 (19 de novembro de 2008): 18970–75. http://dx.doi.org/10.1073/pnas.0804451105.
Texto completo da fonteRehn, Martin, e Anders Lansner. "Sequence memory with dynamical synapses". Neurocomputing 58-60 (junho de 2004): 271–78. http://dx.doi.org/10.1016/j.neucom.2004.01.055.
Texto completo da fonteMitchell, Melanie. "Human Memory: A Dynamical Process". Contemporary Psychology 48, n.º 3 (junho de 2003): 326–27. http://dx.doi.org/10.1037/000805.
Texto completo da fonteBoffetta, G., R. Monasson e R. Zecchina. "MEMORY RETRIEVAL IN OPTIMAL SUBSPACES". International Journal of Neural Systems 03, supp01 (janeiro de 1992): 71–77. http://dx.doi.org/10.1142/s0129065792000401.
Texto completo da fonteAICARDI, FRANCESCA, e SERGIO INVERNIZZI. "MEMORY EFFECTS IN DISCRETE DYNAMICAL SYSTEMS". International Journal of Bifurcation and Chaos 02, n.º 04 (dezembro de 1992): 815–30. http://dx.doi.org/10.1142/s0218127492000458.
Texto completo da fonteKlinshov, Vladimir V., e Vladimir I. Nekorkin. "Dynamical model of working memory system". Neuroscience Research 58 (janeiro de 2007): S44. http://dx.doi.org/10.1016/j.neures.2007.06.259.
Texto completo da fonteBrianzoni, Serena, Cristiana Mammana, Elisabetta Michetti e 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.
Texto completo da fonteOliveira, H. S., A. S. de Paula e 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.
Texto completo da fonteMohapatra, Anushaya, e William Ott. "Memory loss for nonequilibrium open dynamical systems". Discrete & Continuous Dynamical Systems - A 34, n.º 9 (2014): 3747–59. http://dx.doi.org/10.3934/dcds.2014.34.3747.
Texto completo da fonteOtt, William, Mikko Stenlund e Lai-Sang Young. "Memory loss for time-dependent dynamical systems". Mathematical Research Letters 16, n.º 3 (2009): 463–75. http://dx.doi.org/10.4310/mrl.2009.v16.n3.a7.
Texto completo da fonteTeses / dissertações sobre o assunto "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.
Texto completo da fonteKropff, 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.
Texto completo da fonteRehn, 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.
Texto completo da fonteIn 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.
QC 20100916
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.
Texto completo da fonteBauer, 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.
Texto completo da fonteAbbs, Brandon Robert. "The temporal dynamics of auditory memory for static and dynamic sounds". Diss., University of Iowa, 2008. http://ir.uiowa.edu/etd/4.
Texto completo da fonteWilliams, Peter. "Dynamic memory for design". Thesis, The University of Sydney, 1995. https://hdl.handle.net/2123/27472.
Texto completo da fonteSperens, Martin. "Dynamic Memory Managment in C++". Thesis, Luleå tekniska universitet, Datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-76611.
Texto completo da fonteBisht, Pawas. "Disaster and the dynamics of memory". Thesis, Loughborough University, 2013. https://dspace.lboro.ac.uk/2134/14184.
Texto completo da fonteWu, Jiaming. "A modular dynamic Neuro-Synaptic platform for Spiking Neural Networks". Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASP145.
Texto completo da fonteBiological 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
Livros sobre o assunto "Dynamical memory"
Irene, Dorfman, Fokas A. S. 1952- e Gelʹfand I. M, eds. Algebraic aspects of integrable systems: In memory of Irene Dorfman. Boston: Birkäuser, 1997.
Encontre o texto completo da fonteBlokh, Alexander, Leonid Bunimovich, Paul Jung, Lex Oversteegen e 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.
Texto completo da fonteV, Anosov D., Stepin A. M e 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.
Encontre o texto completo da fonteMotorola. Dynamic RAMs & memory modules. 2a ed. Phoenix, AZ: Motorola, 1996.
Encontre o texto completo da fonteKorostelina, Karina V. Memory Sites and Conflict Dynamics. London: Routledge, 2024. http://dx.doi.org/10.4324/9781003497332.
Texto completo da fonteMotorola. Dynamic RAMs and memory modules. Phoenix, AZ: Motorola, 1993.
Encontre o texto completo da fonteAtienza Alonso, David, Stylianos Mamagkakis, Christophe Poucet, Miguel Peón-Quirós, Alexandros Bartzas, Francky Catthoor e Dimitrios Soudris. Dynamic Memory Management for Embedded Systems. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-10572-7.
Texto completo da fonteIncorporated, Advanced Micro Devices. Dynamic memory design data book/handbook. [Sunnyvale, CA]: Advanced Micro Devices, Inc., 1990.
Encontre o texto completo da fonteDaconta, Michael C. C++ pointers and dynamic memory management. New York: Wiley, 1995.
Encontre o texto completo da fonteFarkas, Keith I. Memory-system design considerations for dynamically-scheduled microprocessors. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1997.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "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.
Texto completo da fonteLiu, Jun, e 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.
Texto completo da fonteFung, C. C. Alan, K. Y. Michael Wong e 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.
Texto completo da fonteCosnard, Michel, e 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.
Texto completo da fonteBragov, A. M., L. A. Igumnov, A. Yu Konstantinov, A. K. Lomunov e 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.
Texto completo da fonteGrasselli, Maurizio, e 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.
Texto completo da fonteButaud, Pauline, Morvan Ouisse, Kévin Jaboviste, Vincent Placet e 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.
Texto completo da fonteSoares, O. D. D., A. L. V. S. Lage, A. O. S. Gomes e 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.
Texto completo da fonteKoopmans, 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.
Texto completo da fonteHayashi, Hatsuo, e 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.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Dynamical memory"
Shen, Minghao, e 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.
Texto completo da fonteLoveridge, Tegan, Kai Shinbrough e 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.
Texto completo da fonteOtsuka, Kenju, e 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.
Texto completo da fonteGordon, Goren, e Gershon Kurizki. "Dynamical control of noisy quantum memory channels". In Microtechnologies for the New Millennium, editado por Ali Serpengüzel, Gonçal Badenes e Giancarlo C. Righini. SPIE, 2007. http://dx.doi.org/10.1117/12.723952.
Texto completo da fonteDuda, Alexander M., e 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.
Texto completo da fonteChung-Ming Ou e 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.
Texto completo da fonteAndrianov, Serge N., e 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.
Texto completo da fonteVakhnenko, 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.
Texto completo da fonteAlonso-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.
Texto completo da fonteDavydenko, Alexander A., Natalya V. Raspopova e 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.
Texto completo da fonteRelatórios de organizações sobre o assunto "Dynamical memory"
Beri, A. C., e T. F. George. Memory Effects in Dynamical Many-Body Systems: The Isomnesic (Constant-Memory) Approximation. Fort Belvoir, VA: Defense Technical Information Center, abril de 1985. http://dx.doi.org/10.21236/ada154160.
Texto completo da fontePerdigão, Rui A. P., e Julia Hall. Spatiotemporal Causality and Predictability Beyond Recurrence Collapse in Complex Coevolutionary Systems. Meteoceanics, novembro de 2020. http://dx.doi.org/10.46337/201111.
Texto completo da fonteAsea, Patrick K., e 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.
Texto completo da fonteKim, Joohee, e Marios C. Papaefthymiou. Block-Based Multi-Period Refresh for Energy Efficient Dynamic Memory. Fort Belvoir, VA: Defense Technical Information Center, abril de 2002. http://dx.doi.org/10.21236/ada414244.
Texto completo da fonteLagoudas, Dimitris C. Dynamic Behavior and Shock Absorption Properties of Porous Shape Memory Alloys. Fort Belvoir, VA: Defense Technical Information Center, julho de 2002. http://dx.doi.org/10.21236/ada403775.
Texto completo da fonteSaxena, A., A. R. Bishop, S. R. Shenoy, Y. Wu e T. Lookman. A model of shape memory materials with hierarchical twinning: Statics and dynamics. Office of Scientific and Technical Information (OSTI), julho de 1995. http://dx.doi.org/10.2172/102295.
Texto completo da fonteMayas, Magda. Creating with timbre. Norges Musikkhøgskole, agosto de 2018. http://dx.doi.org/10.22501/nmh-ar.686088.
Texto completo da fonteD`Azevedo, E. F., e C. H. Romine. A new shared-memory programming paradigm for molecular dynamics simulations on the Intel Paragon. Office of Scientific and Technical Information (OSTI), dezembro de 1994. http://dx.doi.org/10.2172/28414.
Texto completo da fonteD'Azevedo, E. F. A New Shared-Memory Programming Paradigm for Molecular Dynamics Simulations on the Intel Paragon. Office of Scientific and Technical Information (OSTI), janeiro de 1995. http://dx.doi.org/10.2172/814063.
Texto completo da fonteVineyard, Craig Michael, e Stephen Joseph Verzi. A Case Study on Neural Inspired Dynamic Memory Management Strategies for High Performance Computing. Office of Scientific and Technical Information (OSTI), setembro de 2017. http://dx.doi.org/10.2172/1396076.
Texto completo da fonte