Image recognition using extended BAM neural networks

In this paper, we present an extended bidirectional associative memory (BAM) neural network approach to image recognition. This approach is characterized by the following important properties due to its associative memory: 1) it has the features of great adaptivity, robustness and fault tolerance to carry out recognition; 2) the recognition system constructed allows for the formation of arbitrary nonlinear decision surfaces; and 3) the recognition system can perform not only the recognition task but also restore the correct information from incomplete even some extent incorrect information at the same time. Experiments are also conducted and the results show that this approach is very efficient and has great application potentials.<>