A learning algortithm for invariance extraction and recognition of unconstrained handwritten digits is proposed in the article.Furthermore,a novel periodic packet activation funnction is suggested to replace the traditional sigmoid activation function to reduce the sensitivity of the extracted features to samples with large variance and to improve the learning speed.Computer simulations show that the proposed algorithm and activation function are effective on extracting features and improving the learning speed and recognition rate.