Character recognition—a review
Pattern Recognition
Fundamentals of neural networks: architectures, algorithms, and applications
Fundamentals of neural networks: architectures, algorithms, and applications
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Self-organizing QRS-wave recognition in ECG using neural networks
IEEE Transactions on Neural Networks
Uncertainty treatment using paraconsistent logic: introducing paraconsistent artificial neural networks
| Hi-index | 0.00 |
In this paper we presented a System capable to realize a recognition of characters with base in the theoretical concepts of the Paraconsistent Annotated Logic. The Paraconsistent Annotated Logic PAL as shown in [1] is a class of the Non-Classic Logic which allows to manipulate contradictory signals. In [5] were presented the Paraconsistent Artificial Neural Cells built with Algorithms based on PAL. These Cells showed the capacity of learning certain signals in form of functions applied in their inputs. In this work, based on these Cells, were made connections and groupings among the algorithms to create a Recognizer of Characters Paraconsistent System (RCPS) capable of to learning and recognizing different types of alphabet letters or sources of signals. After the learning characters, the RPCS can recognize the letter with a high efficiency and further compares it to the group of characters learned previously. The results of tests demonstrate that the RPCS can be used as Specialist Systems of words and images Recognition