Linked Life Data

12487711

Source:http://linkedlifedata.com/resource/pubmed/id/12487711

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2002-12-18
pubmed:abstractText
It is generally known that Morse code is an efficient input method for one or two switches and it is made from long and short sounds separated by silence between the sounds. The long-to-short ratio in the definition is always 3 to 1, but the long-to-short ratio variation for a disabled person is so large that it is difficult to recognize. In the last few years, several Morse code recognition methods have been successfully built on the LMS adaptive algorithms and neural network algorithm. But LMS-related adaptive algorithms need mass computation to infer the characteristic of the controller; also the neural network must learn first, by inputting some data before it is used to recognize the Morse code sequence. In this study, two fuzzy algorithms are used to recognize the unstable Morse code sequences and the result demonstrates a significant improvement of recognition for real time signal processing in a single-chip microprocessor.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0309-1902
pubmed:author
pubmed:issnType
Print
pubmed:volume
26
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
202-7
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:articleTitle
Morse code recognition system with fuzzy algorithm for disabled persons.
pubmed:affiliation
Department of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan, ROC.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't, Evaluation Studies