DocumentCode
2901063
Title
Study on Enhancing Features of Digital Oscilloscope to Measure the Period of Weak FM Signal
Author
Xiaoling, Li ; Xing, Yin
Author_Institution
Inf. Coll., Panzhihua Univ., Panzhihua, China
Volume
3
fYear
2009
fDate
4-5 July 2009
Firstpage
15
Lastpage
18
Abstract
This paper studied a method of applying the principle of chaos and neural network to detect FM modulation signal and calculate the period of the modulated signal. Also it advanced a way to enhance the features of digital oscilloscope (DSO) to measure the period of weak FM signal by programming and embedding it to the function database of DSO. According the characteristic of chaotic time serial, neural network selected Elman network, and constructed it while itpsilas dimensions of input and output were fixed by computing the correlation dimension of the chaotic time serial. Then, making use of the characteristic of identification of space-time of spatio-temporal neural network, it detected directly weak FM signal under chaotic background in chaotic state. Last, it obtained the variational relation of time-amplitude by calculating the frequency-time function. This way break through conventional chaotic measurement principle and is simple to embed in DSO. The experiment testified that it has a widely frequency scope and reliable result.
Keywords
chaos; modulation; neural nets; oscilloscopes; spatiotemporal phenomena; Elman network; chaotic measurement; chaotic time serial; detect FM modulation signal; digital oscilloscope; frequency-time function; function database; modulated signal; space-time identification; spatiotemporal neural network; Chaos; Computer networks; Frequency modulation; Functional programming; Neural networks; Oscilloscopes; Signal detection; Signal processing; Spatial databases; Testing; Chaos; Digital Oscilloscope; FM Modulation; Measurement; Neural Networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Environmental Science and Information Application Technology, 2009. ESIAT 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3682-8
Type
conf
DOI
10.1109/ESIAT.2009.348
Filename
5199626
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