Training partially recurrent neural networks using evolutionary strategies

This correspondence presents the latest results of using evolutionary strategies (ESs) to design partially recurrent neural networks for viseme recognition. ESs are stochastic optimization algorithms based upon the principles of natural selection found in the biological world. Our results indicate that ESs can be effectively used to determine the synaptic weights in neural networks and can outperform backpropagation techniques