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Tactile communication fault tolerance method and system based on compensation type long short-term memory network

A long-short-term memory and network technology, applied in biological neural network models, input/output process of data processing, input/output of user/computer interaction, etc., can solve problems such as poor prediction effect and poor regularity of tactile data changes , to achieve accurate prediction, improved stability, and improved efficiency

Active Publication Date: 2020-11-20
FUZHOU UNIV
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Problems solved by technology

However, the change regularity of the tactile data is poor. When using the original LSTM for prediction, when encountering the sudden change of the slope before and after the tactile data change, the LSTM prediction will have a large error at the inflection point, and continue in the subsequent predictions. or reduce the error value slightly, leading to poor forecasting overall

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[0029] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0030] It should be pointed out that the following detailed description is exemplary and is intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0031] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combina...

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Abstract

The invention relates to a tactile communication fault tolerance method and system based on a compensation type long short-term memory network. According to touch data characteristics, a compensationtype LSTM data prediction model is designed; when data is received, the compensation type LSTM model is utilized to predict and reconstruct data lost or compressed and removed in the communication process, and an original sequence is recovered. The compensation gate is added to compensate the output value, the prediction error is further reduced, and the stability of the touch communication systemis improved.

Description

technical field [0001] The invention relates to the technical field of tactile communication, in particular to a fault-tolerant tactile communication method and system based on a compensated long-short-term memory network. Background technique [0002] With the development of virtual reality (VR) and artificial intelligence, people are gradually unable to be satisfied with the sense of reality and immersion obtained in vision and hearing, so touch has received more and more attention in the industry. During the transmission of haptic data, transmission errors may be caused by problems such as network jitter, which may lead to instability of the haptic communication system. Traditionally, methods such as zero-order hold and first-order linearity are used to solve this problem, but research has shown that haptic data is not just a simple linear relationship. In recent years, due to its advantages in time series prediction, long short-term memory (LSTM) neural network has been...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F3/01G06N3/04
CPCG06F3/016G06N3/044G06N3/045
Inventor 徐艺文林擎旭郑权斐房颖赵铁松
Owner FUZHOU UNIV
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