Study on modeling implicit learning based on MAM framework-Reference-Cited by-同舟云学术

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Study on modeling implicit learning based on MAM framework

Published:2021-05-25 Issue:6 Volume:54 Page:4799-4825
ISSN:0269-2821
Container-title:Artificial Intelligence Review
language:en
Short-container-title:Artif Intell Rev

Author:

Feng Naiqin^ORCID,Geng Xiuqin,Sun Bin

Funder

Key Research and Development Project of Henan Province

the science and technology research project of Zhengzhou city

Key Research Project of Zhengzhou University of Industrial Technology

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Link

https://link.springer.com/content/pdf/10.1007/s10462-021-10019-x.pdf

Reference47 articles.

1. Acevedo ME, Martinez JA, Acevedo MA, Yanez C (2014) Morphological associative memories for gray-scale image encryption. Appl Math Inf Sci 8(1):127–134. https://doi.org/10.12785/amis/080115

2. Acevedo ME, Acevedo MA, Felipe F, Aquino D (2016) Pattern Recognition of mtDNA with Associative Models. MATEC Web Con 68:18002. https://doi.org/10.1051/matecconf/20166818002

3. Arce F, Zamora E, Sossa H, Barron R (2018) Differential evolution training algorithm for dendrite morphological neural networks. Appl Soft Comput J. https://doi.org/10.1016/j.asoc.2018.03.033

4. Brooks LR (1978) Nonanalytic concept formation and memory for instances. In: Rosch E, Lloyd B (eds) Cognition and categorization. Lawrence Elbaum Associates, pp 3–170

5. Brooks LR, Vokey JR (1991) Abstract analogies and abstracted grammars: Comments on Reber (1989) and Mathews et al (1989). J Exp Psychol Learn Mem Cognit 17: 316–323. https://doi.org/10.1037/0096-3445.120.3.316

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