Convolutional neural network compression method and system based on learning automaton and medium

A convolutional neural network and compression method technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as accuracy loss, failure to consider connection correlation, and small compression effect

Inactive Publication Date: 2019-09-10
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

Both have different problems in practical applications, among which the parameter compression effect of encoding compression is small, and the pruning based on weight does not consider the c

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  • Convolutional neural network compression method and system based on learning automaton and medium
  • Convolutional neural network compression method and system based on learning automaton and medium
  • Convolutional neural network compression method and system based on learning automaton and medium

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[0106] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0107] According to a kind of convolutional neural network compression method based on learning automata provided by the present invention, comprising:

[0108] Parameter initialization step: initialize learning automaton parameters;

[0109] State value selection step: according to the obtained initialized learning automaton parameters, each learning automaton selects its own state value according to the preset behavior selection probability, and obtains the state value of each learning automaton;

[01...

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Abstract

The invention provides a convolutional neural network compression method and system based on a learning automaton and a medium. The method comprises a parameter initialization step of initializing theparameters of the learning automaton; a state value selection step of according to the obtained initialized learning automaton parameters, enabling each learning automaton to select a state value ofthe learning automaton according to a preset behavior selection probability to obtain a state value of each learning automaton; and a network structure updating step of updating the network structureaccording to the obtained state value of each learning automaton, and obtaining the updated network structure. According to the method, the learning automaton idea is innovatively used for screening the optimal convolution kernel set in the convolutional neural network, so that the convolutional neural network can complete the network compression task to the maximum extent under the condition of losing a little of classification precision.

Description

technical field [0001] The present invention relates to the fields of deep learning and artificial intelligence, in particular to a convolutional neural network compression method, system and medium based on learning automata. In particular, it relates to a convolutional neural network compression method based on Learning Automata (LA). Background technique [0002] Convolutional neural network is a mathematical model that can simulate complex functions. It belongs to the feedforward neural network in deep learning. This model gradually converts the initial features of the input data into advanced features through a multi-layer network, and then combined with subsequent related operations can Complete complex classification learning tasks. [0003] Convolutional neural network is currently mainly used in the field of image processing. It imitates the human visual processing process through multi-layer convolution and pooling. The effect of scale transformation is to form m...

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Application Information

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IPC IPC(8): G06N3/04G06N3/08
CPCG06N3/082G06N3/047G06N3/045
Inventor 李生红冯帅郭浩楠
Owner SHANGHAI JIAO TONG UNIV
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