DocumentCode :
2835797
Title :
Research on amplifier performance evaluation based on feature double weighted support vector machine
Author :
Zhang, Aihua
Author_Institution :
Coll. of Inf. Sci. & Eng., BoHai Univ., Jinzhou, China
fYear :
2010
fDate :
26-28 May 2010
Firstpage :
806
Lastpage :
809
Abstract :
An evaluation for amplifier performance based on feature double weighted support vector machine was proposed in this paper. The evaluation system structure was conformed, relied on the college analog electronic technology experiments, adopted the amplifier performance four indexes obtained via amplitude-frequency tester in one year to construct training set, and then to be four classifier evaluation based on FDWSVM. Experiment results show that this method can improve the parameter test precision and is suitable for the evaluation of electronic products.
Keywords :
amplifiers; statistical analysis; support vector machines; amplifier performance evaluation; amplitude-frequency tester; college analog electronic technology experiments; feature double weighted support vector machine; parameter test precision; Cutoff frequency; Educational institutions; Electronic equipment testing; Frequency conversion; Instruments; Kernel; Machine learning; Pulse amplifiers; Support vector machine classification; Support vector machines; Amplifier Performance Evaluation; Classifier; FDWSVM;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
Type :
conf
DOI :
10.1109/CCDC.2010.5498115
Filename :
5498115
Link To Document :
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