Cornelio Yáñez-Márquez

Learn More
Software estimation has been identified as one of the three great challenges for half-century-old computer science. Developers should be able to achieve practices containing effort estimation based on their own programs. New paradigms as fuzzy logic may offer an alternative for software effort estimation. This paper describes an application whose results(More)
In this work a new Bidirectional Associative Memory model, surpassing every other past and current model, is presented. This new model is based on Alpha–Beta associative memories, from whom it inherits its name. The main and most important characteristic of Alpha–Beta bidirectional associative memories is that they exhibit perfect recall of all patterns in(More)
Regression analysis to generate predictive equations for software development effort estimation has recently been complemented by analyses using less common methods such as fuzzy logic models. On the other hand, unless engineers have the capabilities provided by personal training, they cannot properly support their teams or consistently and reliably produce(More)
A new model for associative memories is proposed in this paper. The mathematical tools used in this new model, include two binary operators designed specifically for the memories developed here. These operators were arbitrarí/y named as the .first two letters from the Greek alphabet: a and fJ. The new associative memories (afJ)are oftwo kinds and are able(More)
Bidirectional Associative Memories (BAM) based on Kosko’s model are implemented through iterative algorithms and present stability problems. Also, these models along with other models based on different methods, have not been able to perfectly recall all trained patterns. In this paper we present an English-Spanish / Spanish-English translator based on a(More)
Classification is one of the key issues in medical diagnosis. In this paper, a novel approach to perform pattern classification tasks is presented. This model is called Associative Memory based Classifier (AMBC). Throughout the experimental phase, the proposed algorithm is applied to help diagnose diseases; particularly, it is applied in the diagnosis of(More)