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Relevant bibliographies by topics / Dynamical memory

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Journal articles

Academic literature on the topic 'Dynamical memory'

Author: Grafiati

Published: 14 December 2024

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Journal articles on the topic "Dynamical memory"

1

Ganguli, S., D. Huh, and H. Sompolinsky. "Memory traces in dynamical systems." Proceedings of the National Academy of Sciences 105, no. 48 (2008): 18970–75. http://dx.doi.org/10.1073/pnas.0804451105.

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2

Rehn, 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.

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3

Mitchell, Melanie. "Human Memory: A Dynamical Process." Contemporary Psychology 48, no. 3 (2003): 326–27. http://dx.doi.org/10.1037/000805.

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4

Boffetta, G., R. Monasson, and R. Zecchina. "MEMORY RETRIEVAL IN OPTIMAL SUBSPACES." International Journal of Neural Systems 03, supp01 (1992): 71–77. http://dx.doi.org/10.1142/s0129065792000401.

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A simple dynamical scheme for Attractor Neural Networks with non-monotonic three state effective neurons is discussed. For the unsupervised Hebb learning rule, we give some basic numerical results which are interpreted in terms of a combinatorial task realized by the dynamical process (dynamical selection of optimal subspaces). An analytical estimate of optimal performance is given by resorting to two different simplified versions of the model. We show that replica symmetry breaking is required since the replica symmetric solutions are unstable.

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5

AICARDI, FRANCESCA, and SERGIO INVERNIZZI. "MEMORY EFFECTS IN DISCRETE DYNAMICAL SYSTEMS." International Journal of Bifurcation and Chaos 02, no. 04 (1992): 815–30. http://dx.doi.org/10.1142/s0218127492000458.

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Let fµ(s)=µs(1−s) be the family of logistic maps with parameter µ, 1≤µ≤4. We present a study of the second-order difference equation xn+1=fµ([1−∈]xn+∈xn−1), 0≤∈≤1, which reduces to the well-known logistic equation as ∈=0.

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6

Klinshov, 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.

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7

Brianzoni, 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.

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We consider the dynamics of a stochastic cobweb model with linear demand and a backward-bending supply curve. In our model, forward-looking expectations and backward-looking ones are assumed, in fact we assume that the representative agent chooses the backward predictor with probability , and the forward predictor with probability , so that the expected price at time is a random variable and consequently the dynamics describing the price evolution in time is governed by a stochastic dynamical system. The dynamical system becomes a Markov process when the memory rate vanishes. In particular, we study the Markov chain in the cases of discrete and continuous time. Using a mixture of analytical tools and numerical methods, we show that, when prices take discrete values, the corresponding Markov chain is asymptotically stable. In the case with continuous prices and nonnecessarily zero memory rate, numerical evidence of bounded price oscillations is shown. The role of the memory rate is studied through numerical experiments, this study confirms the stabilizing effects of the presence of resistant memory.

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8

Oliveira, 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.

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The dynamical response of systems with shape memory alloy (SMA) elements presents a rich behavior due to their intrinsic nonlinear characteristic. SMA’s nonlinear response is associated with both adaptive dissipation related to hysteretic behavior and huge changes in properties caused by phase transformations. These characteristics are attracting much technological interest in several scientific and engineering fields, varying from medical to aerospace applications. An important characteristic associated with dynamical response of SMA system is the jump phenomenon. Dynamical jumps result in abrupt changes in system behavior and its analysis is essential for a proper design of SMA systems. This paper discusses the nonlinear dynamics of a one degree of freedom SMA oscillator presenting pseudoelastic behavior and dynamical jumps. Numerical simulations show different aspects of this kind of behavior, illustrating its importance for a proper understanding of nonlinear dynamics of SMA systems.

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9

Mohapatra, 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.

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10

Ott, 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.

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