Name
Abstract | ||
|---|---|---|
Points out that SaPOSM integrates an efficient deterministic optimization algorithm, called POSM, with the popular stochastic optimization paradigm simulated annealing (SA). It offers great promise for improving the optimization results significantly while using only a moderate amount of computing time. Tested on a suite of multi-minima optimization benchmark problems, SaPOSM's performance rivals a recently reported fast simulated diffusion method. SaPOSM was used to extract the parameters of state-of-the-art submicron (0.3-μm channel length) MOSFET transistors, and very favorable results have been obtained. For a second difficult parameter extraction problem (18 parameters, five different channel lengths), simulation results indicate that SaPOSM achieves performance comparable to the SA method. Specifically, both SA and SaPOSM are able to minimize the modeling error to several orders of magnitude smaller than that obtained using POSM alone. At the same time, the computing time taken by SaPOSM is only a very small fraction of that taken by the SA method |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1109/43.256940 | IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems |
Keywords | DocType | Volume |
popular stochastic optimization paradigm,semiconductor device models,MOSFET models,SaPOSM,sa method,different channel length,channel length,parameter extraction,0.3 micron,simulated diffusion method,mosfet model,optimization result,insulated gate field effect transistors,computing time,efficient deterministic optimization algorithm,performance rival,stochastic optimization paradigm simulated annealing,optimization method,multi-minima optimization benchmark problem,simulated annealing,deterministic optimization algorithm,multi-minima optimization benchmark problems,m channel length,modeling error | Journal | 12 |
Issue | ISSN | Citations |
10 | 0278-0070 | 0 |
PageRank | References | Authors |
0.34 | 10 | 2 |