Research on dynamic routing algorithm based on gaussian mixture model

Author:

Huang Yuzhan

Abstract

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.

Publisher

EDP Sciences

Subject

General Medicine

Reference5 articles.

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4. Sabour S, Frosst N, Hinton G E. Dynamic routing between capsules [A]. Advanced in Neural information processing systems [C]. US:NIPS, 2017.3856-3866.

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1. Research and Development of a Sound Pattern Classifier in Complex Urban Acoustic Environments;2024 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF);2024-06-03

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