The invention relates to a promotion network self-enhanced image voice
deep learning model. According to the application, a promotion scheme and a neural
network structure are fused to design a
deep learning architecture which can realize autonomous learning of network parameters and modules and is compatible with
linearity and nonlinearity, and the
system stability is improved; linear and nonlinear promotion schemes are combined with a
neural network classification model through loosening and compacting to construct a
deep learning classification model, and the generalization ability is high; the
convolution layer and the
pooling layer are autonomously combined in the aspect of the
network structure, a fully promoted network is realized, and grading
processing has a better effect in classification and
estimation of reasoning tasks; in the aspect of network operation,
convolution operation and
pooling operation are achieved through promotion, unification of
linearity and nonlinearity is achieved, and the calculation complexity is low; in the network training process, hierarchical low entropy is adopted to accelerate network training, so that the network retains the
learnability of
convolution, a
pooling layer becomes learnable, the
model learning ability is strong, the error is smaller than that of the method in the prior art, and the accuracy and robustness of image
speech recognition and classification are better.