Fuzzy support vector machines for adaptive Morse code recognition.
Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, facilitating mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. Therefore, an adaptive automatic recognition method with a high recognition rate is needed. The proposed system uses both fuzzy support vector machines and the variable-degree variable-step-size least-mean-square algorithm to achieve these objectives. We apply fuzzy memberships to each point, and provide different contributions to the decision learning function for support vector machines. Statistical analyses demonstrated that the proposed method elicited a higher recognition rate than other algorithms in the literature.
Yang
Cheng-Hong
CH
Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 807, Taiwan. chyang@cc.nkit.edu.tw
Jin
Li-Cheng
LC
Chuang
Li-Yeh
LY
D000465:Algorithms; D001185:Artificial Intelligence; D003143:Communication Devices for People with Disabilities; D017143:Fuzzy Logic; D006801:Humans; D015233:Models, Statistical; D016571:Neural Networks, Computer; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated; D021641:Recognition, Psychology; D012815:Signal Processing, Computer-Assisted; D012984:Software; D014584:User-Computer Interface; D015443:Word Processing