MATEC Web Conf.
Volume 355, 20222021 International Conference on Physics, Computing and Mathematical (ICPCM2021)
|Number of page(s)||8|
|Section||Computing Methods and Computer Application|
|Published online||12 January 2022|
Research on dynamic routing algorithm based on gaussian mixture model
University of Electronic Science and Technology of China, Chengdu, China
* Corresponding author: firstname.lastname@example.org
In this paper, based on the method of environmental sound detection, a neural network model based on capsule network and Gaussian mixture model is proposed. The model proposed in this paper mainly aims at the disadvantages of dynamic routing algorithm in the capsule network, and proposes a dynamic routing algorithm based on Gaussian mixture model. The improved dynamic routing algorithm assumes that the characteristics of the data conform to the multi-dimensional Gaussian distribution, so the model can learn the distribution of data features by building distribution functions of different classes. The information entropy is used as the activation value of the salient degree of the feature. Through experiments, the accuracy of the proposed algorithm on Urbansound8K data set is more than 92%, which is 4.8% higher than the original algorithm.
Key words: Capsule net / Dynamic routing algorithm / Gaussian mixture model
© The Authors, published by EDP Sciences, 2022
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