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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
511

Adaptive Power Analog-to-Digital Interface for Digital Systems

Grimes, Todd S. January 2016 (has links)
No description available.
512

Utilization of a Neural Network to Improve Fuel Maps of an Air-Cooled Internal Combustion Engine

Young, Ryan F. 23 September 2010 (has links)
No description available.
513

DESIGN FOR TRANSFERABILITY

CHAUDHURI, PARTHA SUBIR 24 June 2008 (has links)
No description available.
514

Supporting Fault Tolerance and Dynamic Load Balancing in FREERIDE-G

Bicer, Tekin 23 August 2010 (has links)
No description available.
515

Cognitive Systems Engineering as an Ontology for Design

Tan, Kok Keng 25 August 2010 (has links)
No description available.
516

Improving the Environmental Performance of Manufacturing Systems via Exergy, Techno-ecological Synergy, and Optimization

Grubb, Geoffrey Francis 30 July 2010 (has links)
No description available.
517

Evaluation of User Satisfaction with a Clinical Genetics Database

Oriyo, Ferry 03 September 2010 (has links)
No description available.
518

Perspective Control: Technology to Solve the Multiple Feeds Problem in Sensor Systems

Morison, Alexander M. 25 October 2010 (has links)
No description available.
519

Voltage-source inverter output waveform compensation using adaptive intelligent control

Barnes, Lemuel Gregory III 19 October 2006 (has links)
A single-layer neural network-based voltage compensation technique which generates minimum-distortion sinusoidal output voltages from a three-phase PWM inverter used for uninterruptible power supplies (UPS) is described. The proposed compensation technique is implemented in a microprocessor-based controller constructed in the stationary d-q frame where the controller sampling rate is twice the inverter switching frequency. The structure of a feed-forward artificial neural network connects network inputs and outputs through multiple linear or nonlinear neuron models, and processes these input/output data associations in a parallel distributed manner. Network inputs in the form of UPS load voltage commands and load current feedback are propagated forward in the network each controller sampling period generating the inverter output voltage commands, the network outputs, which are converted to three phase inverter switching Signals using the space vector PWM waveform generation process. / Ph. D.
520

Effect of pictorial icon interface on user-learner performance

Kunnath, Maria Lorna Azul 01 July 2001 (has links)
No description available.

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