Title :
Neuro-genetic design centering of millimeter wave oscillators
Author :
Sen, P. ; Pratap, R.J. ; Mukhopadhyay, R. ; Sarkar, S. ; Lee, C.-H. ; Pinel, S. ; May, G.S. ; Laskar, J.
Author_Institution :
Sch. of ECE, Georgia Inst. of Technol., Atlanta, GA
Abstract :
In this paper, a new technique for design centering and the yield enhancement of millimeter-wave (MMW) circuits is presented using neural networks for circuit modeling and genetic algorithms for parametric yield optimization. A Monte Carlo based method is developed for the yield estimation utilizing the neural network models. The neuro-genetic methodology has been used for the design centering of 30 GHz cross-coupled VCO as well as a fixed-frequency 60 GHz oscillator. The results display significant yield enhancement i.e. 8% to 91% for 30 GHz VCO and 7% to 70% for the 60 GHz oscillator
Keywords :
Monte Carlo methods; circuit CAD; circuit optimisation; genetic algorithms; integrated circuit design; millimetre wave oscillators; neural nets; voltage-controlled oscillators; 30 GHz; 60 GHz; Monte Carlo based method; circuit modeling; cross-coupled VCO; fixed-frequency oscillator; genetic algorithms; millimeter wave oscillators; millimeter-wave circuits; neural networks; neuro-genetic design centering; parametric yield optimization; voltage controlled oscillator; yield enhancement; Algorithm design and analysis; Design optimization; Displays; Genetic algorithms; Millimeter wave circuits; Millimeter wave technology; Monte Carlo methods; Neural networks; Voltage-controlled oscillators; Yield estimation;
Conference_Titel :
Silicon Monolithic Integrated Circuits in RF Systems, 2006. Digest of Papers. 2006 Topical Meeting on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-9472-0
DOI :
10.1109/SMIC.2005.1587929
