Reducing the requirements for the corrective ability of classical codes with error detection and correction using preliminary neural network enrichment of biometric data
Background. Obtaining numerical estimates of the corrective ability of classical codes with high redundancy and neural network corrective structures by the example of controlling 416 biometric parameters of the handwritten password word “Penza”. Materials and methods. It is proposed to use the er...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Penza State University Publishing House
2022-12-01
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| Series: | Известия высших учебных заведений. Поволжский регион:Технические науки |
| Subjects: |