Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

V Protopopescu

Showing results (1-10 of 5) with videos related to

Pageof 1
Sort By:
Chaos (Woodbury, N.Y.)|June 11, 2004
Non-Lipschitzian control algorithms for extended mechanical systemsV Protopopescu, J Barhen
Applied Optics|June 5, 2010
Optimization of the computational load of a hypercube supercomputer onboard a mobile robotJ Barhen, N Toomarian, V Protopopescu
Physical Review Letters|April 12, 2003
Control of friction at the nanoscaleY Braiman, J Barhen, V Protopopescu
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|June 6, 2003
Optimal control of the transient behavior of coupled solid-state lasersE Jung, S Lenhart, V Protopopescu, et al.
IEEE Transactions on Neural Networks|January 1, 1996
Learning algorithms for feedforward networks based on finite samplesN V Rao, V Protopopescu, R C Mann, et al.
Pageof 1

Showing results (1-10 of 5) with videos related to

Sort By:
Pageof 1
Chaos (Woodbury, N.Y.)|June 11, 2004
Non-Lipschitzian control algorithms for extended mechanical systemsV Protopopescu, J Barhen
Applied Optics|June 5, 2010
Optimization of the computational load of a hypercube supercomputer onboard a mobile robotJ Barhen, N Toomarian, V Protopopescu
Physical Review Letters|April 12, 2003
Control of friction at the nanoscaleY Braiman, J Barhen, V Protopopescu
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|June 6, 2003
Optimal control of the transient behavior of coupled solid-state lasersE Jung, S Lenhart, V Protopopescu, et al.
IEEE Transactions on Neural Networks|January 1, 1996
Learning algorithms for feedforward networks based on finite samplesN V Rao, V Protopopescu, R C Mann, et al.
Pageof 1