Data Recognition Processing System for Silent Communication

Abstract

The invention belongs to the field of data identification, and specifically relates to a silent communication data identification processing system, comprising the following steps: 1) establishing a table in Matlab, the table is used to store 26 English letters and their corresponding Morse codes; 2) After MATLAB receives a series of complete signals, it first divides the entire series of signals into signal units, and then smooths the signals to remove subtle noises; 3) Next, it performs differential calculation on the original signals; 4) Finally, it compares with the recorded signals Library comparison, find the matching text information, and realize the signal output. For the first time, the present invention uses mechanical vibration signals instead of traditional neural signals in the SSI field. Combining the advantages of mechanical vibration signals, a new silent communication data recognition and processing system is developed. Users can output without sound and interference. Signal.

Description

technical field [0001] The invention belongs to the field of data identification, and in particular relates to a silent communication data identification processing system. Background technique [0002] With the development of science and technology, the forms of communication have also become rich and diverse. For the communication requirements of multiple environments, the traditional communication technology relying on voice communication can no longer meet the needs of information transmission. For example, in noisy public places, noises such as traffic, noisy crowds, and advertisements in shop windows will seriously interfere with the communication between people, so that information cannot be received accurately and clearly; when encountering danger, shout loudly Calling for help may sometimes expose one's position, irritate criminals or even make people fall into a more unfavorable situation; and when natural disasters such as earthquakes and fires occur, the weak cal...

AI Technical Summary

Problems solved by technology

These methods have helped the experimenters to achieve silent communication to a certain extent, but due to the complexity of the equipment in actual use, it is not convenient to carry; the position of signal collection needs to be precisely controlled, and the deviation of the position will have a great adverse effect, which limits the use of personnel At the same time, for BCI, the complexity of brain activity makes the process of signal acquisition and translation susceptible to interference from human emotions and cannot obtain accurate information

In addition, the existing SSI methods also involve a very complicated learning process. Experimenters need to try repeatedly to realize the expression of simple signals and can only be used in laboratories at present. These problems limit the practical application of SSI.

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