Title :
Efficient optimization of a Ka-Band MMIC sub-harmonically pumped image rejection diode mixer
Author :
Xu, Y. ; Guo, Y. ; Xu, R. ; Yan, B. ; Liu, G.
Author_Institution :
Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu
Abstract :
An efficient optimization technique, support vector regression (SVR) approach, is proposed for designing of Ka-band MMIC sub-harmonically pumped image rejection diode mixer. This SVR approach comes from the support vector machine (SVM) learning theory, which is based on the structural risk minimization (SRM) principle and leads good generalization ability. With this method, a Ka-band MMIC 4th harmonic image rejection diode mixer is designed using comercial United Monolithic Semiconductors process. Details of design approach and outcome of performance simulations is presented.
Keywords :
MMIC mixers; learning (artificial intelligence); minimisation; regression analysis; support vector machines; Ka-Band MMIC sub-harmonically pumped image rejection diode mixer; optimization technique; structural risk minimization principle; support vector machine learning theory; support vector regression; united monolithic semiconductors process; Capacitors; Circuit simulation; Design engineering; Design optimization; MMICs; Mixers; RF signals; Radio frequency; Semiconductor diodes; Support vector machines;
Conference_Titel :
Microwave and Millimeter Wave Technology, 2008. ICMMT 2008. International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-1879-4
Electronic_ISBN :
978-1-4244-1880-0
DOI :
10.1109/ICMMT.2008.4540538
