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Bibliografias temáticas / Neural network adaptation / Livros

Livros sobre o tema "Neural network adaptation"

Siga este link para ver outros tipos de publicações sobre o tema: Neural network adaptation.

Autor: Grafiati

Publicado: 25 de maio de 2024

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Veja os 17 melhores livros para estudos sobre o assunto "Neural network adaptation".

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1

Lee, Tsu-Chang. Structure level adaptation for artificial neural networks. Boston: Kluwer Academic Publishers, 1991.

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2

Lee, Tsu-Chang. Structure Level Adaptation for Artificial Neural Networks. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-3954-4.

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3

Lee, Tsu-Chang. Structure Level Adaptation for Artificial Neural Networks. Boston, MA: Springer US, 1991.

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4

Stonier, Russel J., e Xing Huo Yu. Complex systems: Mechanism of adaptation. Amsterdam: IOS Press, 1994.

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5

Neuronal adaptation theory: Including 29 exercises with solutions, 43 essential ideas, and 108 partially couloured figures, experiment explanations, and general theorems. Frankfurt am Main: Peter Lang, 1996.

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6

1931-, Haykin Simon S., ed. Kalman filtering and neural networks. New York: Wiley, 2001.

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7

J, Stonier Russel, e Xing Huo-yu, eds. Complex systems: Mechanism of adaptation. Amsterdam: IOS Press, 1994.

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8

Focus, Symposium on Learning and Adaptation in Stochastic and Statistical Systems (2001 Baden-Baden Germany). Proceedings of the Focus Symposium on Learning and Adaptation in Stochastic and Statistical Systems. Windsor, Ont: International Institute for Advanced Studies in Systems Research and Cybernetics, 2002.

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9

Marcello, Pucci, e Vitale Gianpaolo, eds. Power converters and AC electrical drives with linear neutral networks. Boca Raton: CRC Press, 2012.

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10

Channel-Mismatch Compensation in Speaker Identification Feature Selection and Adaptation with Artificial Neural Networks. Storming Media, 1998.

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11

(Editor), R. J. Stonier, e Xing Huo Yu (Editor), eds. Complex Systems: Mechanism of Adaptation,. Ios Pr Inc, 1994.

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12

Kilpatrick, Zachary. Spatiotemporal dynamics of neuronal networks with synaptic depression: Spatially structured waves and oscillations in neuronal networks with synaptic depression and adaptation. VDM Verlag Dr. Müller, 2011.

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13

Yanchuk, Serhiy, Viktor Jirsa, Joana Cabral, Oleksandr Popovych e Alessandro Torcini, eds. From Structure to Function in Neuronal Networks: Effects of Adaptation, Time-Delays, and Noise. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-88976-138-8.

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14

Herman, James P. Limbic Pathways to Stress Control. Editado por Israel Liberzon e Kerry J. Ressler. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190215422.003.0008.

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Resumo:

Appropriate control of the HPA (hypothalamo-pituitary-adrenocortical axis) is required for adaptation to physiological and environmental challenges. Inadequate control is linked to numerous stress-related pathologies, including PTSD, highlighting its importance in linking physiological stress responses with behavioral coping strategies. This chapter highlights neurocircuit mechanisms underlying HPA axis adaptation and pathology. Control of the HPA stress response is mediated by the coordinated activity of numerous limbic brain regions, including the prefrontal cortex, hippocampus, and amygdala. In general, hippocampal output inhibits anticipatory HPA axis responses, whereas amygdala subnuclei participate in stress activation. The prefrontal cortex plays an important role in inhibition of context-dependent stress responses. These regions converge on subcortical structures that relay information to paraventricular nucleus corticotropin-releasing hormone neurons, controlling the magnitude and duration of HPA axis stress responses. The output of these neural networks determines the net effect on glucocorticoid secretion, both within the normal adaptive range and in pathological circumstances.

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15

Sebbane, Yasmina Bestaoui. Multi-UAV Planning and Task Allocation. Taylor & Francis Group, 2020.

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16

Sebbane, Yasmina Bestaoui. Multi-UAV Planning and Task Allocation. Taylor & Francis Group, 2020.

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17

Multi-UAV Planning and Task Allocation. Taylor & Francis Group, 2020.

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