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An Implicit Memory-Based Method for Supervised Pattern Recognition
- Source :
- Discrete Dynamics in Nature and Society, Vol 2021 (2021)
- Publication Year :
- 2021
- Publisher :
- Hindawi, 2021.
-
Abstract
- How the human brain does recognition is still an open question. No physical or biological experiment can fully reveal this process. Psychological evidence is more about describing phenomena and laws than explaining the physiological processes behind them. The need for interpretability is well recognized. This paper proposes a new method for supervised pattern recognition based on the working pattern of implicit memory. The artificial neural network (ANN) is trained to simulate implicit memory. When an input vector is not in the training set, the ANN can treat the input as a “do not care” term. The ANN may output any value when the input is a “do not care” term since the training process needs to use as few neurons as possible. The trained ANN can be expressed as a function to design a pattern recognition algorithm. Using the Mixed National Institute of Standards and Technology database, the experiments show the efficiency of the pattern recognition method.
- Subjects :
- 0209 industrial biotechnology
Artificial neural network
Article Subject
Computer science
business.industry
media_common.quotation_subject
Process (computing)
Value (computer science)
Pattern recognition
02 engineering and technology
Term (time)
020901 industrial engineering & automation
Modeling and Simulation
Pattern recognition (psychology)
QA1-939
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Implicit memory
Artificial intelligence
Function (engineering)
business
Mathematics
media_common
Interpretability
Subjects
Details
- Language :
- English
- ISSN :
- 10260226
- Database :
- OpenAIRE
- Journal :
- Discrete Dynamics in Nature and Society
- Accession number :
- edsair.doi.dedup.....ec5679552b1801d1217e9d2f90e8e37f
- Full Text :
- https://doi.org/10.1155/2021/4472174