  The use of deep neural network for decoding error control code will encounter
two problems, namely, the high-precision requirements of the error control code
and the complexity of the neural network due to the long code. In this paper, a
deep neural network decoder is proposed to solve the decoding problem of long
code by using the nature of convolutional code window decoding. A deep neural
network decoder is utilized as a weak classifier, and an integrated decoder is
proposed to improve the decoding performance greatly. The Viterbi decoder is
improved by approximately 2 db at a bit error rate of level 5. Both decoder
methods proposed in this paper can be decoded in parallel and are suitable for
high-bit-rate applications. This study reveals that the accuracy of neural
networks can reach level 8 more.
