Publicación

Tipo de publicación: Artículos científicos (Publicados en revistas de divulgación o científicas)

Título del artículo: Binary associative memories with complemented operations

Registrado por: International Journal of Applied Mathematics and Computer Science

Año de publicación: 2023

Resumen: Associative memories based on lattice algebra are of great interest in pattern recognition applications due to their excellent storage and recall properties. In this paper, a class of binary associative memory derived from lattice memories is presented, which is based on the definition of new complemented binary operations and threshold unary operations. The new learning method generates memories M and W; the former is robust to additive noise and the latter is robust to subtractive noise. In the recall step, the memories converge in a single step and use the same operation as the learning method. The storage capacity is unlimited, and in autoassociative mode there is perfect recall for the training set. Simulation results suggest that the proposed memories have better performance compared to other models.

Editorial:

Número de páginas:

Autor(es): Arturo Gamino-Carranza

Campo: Ciencias de la Computación

Disciplina: Inteligencia Artificial

Subdisciplina: Memorias Asociativas

Número de registro: DOI: 10.34768/amcs-2023-0019