A New Fusion Method of Table Tennis Sensor Information System

• Main Authors: Ji PING, Ding ZHIYI
• Format: Article
• Language: English
• Published: IFSA Publishing, S.L. 2013-12-01
• Series: Sensors & Transducers
• Subjects: Table tennis sensor; Training data; Fusion of information; Data vector model.
• Online Access: http://www.sensorsportal.com/HTML/DIGEST/december_2013/PDF_vol_160/P_1642.pdf

We have collected Table Tennis Training data by sensor System to improve training level. Table Tennis Sensor System analytical methods must be better designed, including definitions, analysis principles, and Information Fusion to avoid inconsistent vocabulary and potentially incorrect interpretation of training data. A continuing problem for Information Fusion of Table Tennis Sensor (TTS) is to develop efficient information unit. Many experts see information fusion as an important solution. The quality of TTS information fusion include establishing and maintaining a database of Table Tennis training information, searching for applicable information to be fused in a design, as well as adapting information toward a proper structure. In this paper, a new Data Vector Model (DVM) method is suggested here for training data classification and fusion of Table Tennis training data. We found that this new method gives a higher accuracy in training data selection and fusion process of TTS compared to the existing formal methods. We can improve the level of Table Tennis training by this method.