Browsing JPL TRS 1992+ by Title

Now showing items 13525-13544 of 27243

M0/Na***subx***TiO***sub2*** Mixed Conducting Electrodes for the Alkali Metal Thermal to Electric Converter

Ryan, M.; Williams, R.; Fiebig, B.; Kisor, A.; Cortez, R.; Homer, M.; Shields, V. (2000-05-14)
M1 mirror print-thru investigation and performance on the thermo-opto-mechanical testbed for the Space Interferometry Mission

Feria, V. Alfonso; Lam, Jonathan; Van Buren, Dave (Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2006., 2006-05-24)

This paper presents the studies carried out to determine the source of the surface distortions on the M1 mirror as well as comparison and model validation during testing. This research was carried out at the Jet Propulsion ...
The M9.0 Tohoku and M6.3 Christchurch earthquakes : what we’ve learned about the capabilities and limits of space geodesy.

Owen, Susan; Simons, Mark; Webb, Frank; Yun, Sang-Ho; Fielding, Eric; Cruz, Jennifer (Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2011., 2011-09-28)
MACH Filter Synthesizing for Detecting Targets in Cluttered Environment for Gray-Scale Optical Correlator

Zhou, H.; Chao, T-H. (1999-04-05)
MACHETE: environment for space networking evaluation

Jennings, Esther; Segui, John; Woo, Simon; Clare, Loren (Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2010, 2010-04-25)
MACHETE: environment for space networking evaluation

Jennings, Esther H.; Segui, John S.; Woo, Simon (Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2010, 2010-04-25)

Space Exploration missions requires the design and implementation of space networking that differs from terrestrial networks. In a space networking architecture, interplanetary communication protocols need to be designed, ...
Machine learning and instrument autonomy

Bue, Brian; Estlin, Tara; Altinok, Alphan; Burl, Mike; Chu, Selina; Doran, Gary; Granat, Rob; Huffman, William; Kiran, Ravi; Mandrake, Lukas; Rebbapragada, Umaa; Tang, Benyang; Wagstaff, Kiri (Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2016, 2016-01-11)
Machine learning chalenges in Mars rover traverse science

Castano, R.; Judd, M.; Anderson, R. C.; Estlin, T. (2003-08-21)
Machine learning challenges in Mars rover traverse science

Castano, R.; Judd, M.; Anderson, R. C.; Estlin, T. (2003-08-21)

The successful implementation of machine learning in autonomous rover traverse science requires addressing challenges that range from the analytical technical realm, to the fuzzy, philosophical domain of entrenched belief ...
Machine learning for exploring data streams, with lessons from the very long baseline array

Thompson, David R. (Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2012., 2012-06-06)
Machine learning methods for real time and archival classification of astronomical transients and variables

Rebbapragada, Umaa (Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2012., 2012-03-01)
Machine Vision Algorithms for Autonomous Small Body Navigation

Johnson, A.; Matthies, L.; SanMartin, A. (1999-09-21)

Due to the small size, irregular shape and variable surface properties of small bodies, accurate motion and position estimation is needed for safe and precise small body exploration.
Machine Vision for Autonomous Small Body Navigation

Johnson, A.; Chen, Y.; Matthies, L.H. (1999-03-20)

This paper describes machine vision algorithms that enable precision guidance and hazard avoidance during small body exploration through onboard visual feature tracking and landmark recognition.
Macroservers: a new high-level programming and execution model for PIM-based scalable architectures

Zima, H. P. (2002)
Macsigma0 ??ftware for Image Display and Analysis on the Macintosh

Norikane, L.; Freeman, A. (1993-08)

This paper describes the software developed at JPL for displaying calibrated SAR images and analyzing them on the Macintosh.
Maerstro path to flight study

Some, Rafi; Geer, Dwight; Lee, Alan (Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2011., 2011-05-23)
Magellan In Transition

Doody, D. (1993)

NASA's Magellan has project mapped 98 percent of Venus' surface with synthetic-aperture imaging radar, microwave radiometry, and radar altimetry.
Magellan Mission Progress Report

Thompson, T. (1994-03-14)
Magellan Mission Progress Report

Saunders, R.S.; Griffith, D.G.; (JPL/Caltech), Magellan Flight Team (1994-07-30)
Magellan Mission Report: The Final Chapter

Thompson, T. (1994-12-05)

Now showing items 13525-13544 of 27243

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