Results 1 - 10 of 66,925

Table 13: Genetic Algorithm Optimization Results Step ACP3L ACP3H

in Pre-Distortion with Narrowband Feedback using Genetic Algorithms Approved by:
by Dr. J. Stevenson Kenney, Dr. G. Tong Zhou, Dr. William, M. Leach, Khimetrics Inc 2005
"... In PAGE 96: ... The optimal solutions are validated over the entire frame of data after the completion of each step described above. These actual ACP optimization results are summarized in Table13 and the sequential linearization performance is illustrated in Figure 52. Table 13: Genetic Algorithm Optimization Results Step ACP3L ACP3H... ..."

Table 2. Genetic algorithm (optimized power)/(initial power) for fixed compile time

in A Period Graph Throughput Estimator for Multiprocessor Systems
by Neal K. Bambha, Shuvra S. Bhattacharyya 2000
"... In PAGE 13: ... For the largest graph, the fixed simulation time was not long enough to make much improvement, but the best result occurred for , where the simulations are less frequent. Table2 summarizes the power reduction for the genetic algorithm with and without using the period graph, with a fixed compile time of one hour. 9 Conclusion This paper has explored a period graph model that enables efficient voltage scaling optimization for self-timed implementations of iterative applications.... ..."
Cited by 2

Table 2. Genetic algorithm (optimized power)/(initial power) for fixed compile time

in A Joint Power/Performance Optimization Algorithm for Multiprocessor Systems using a Period Graph Construct
by unknown authors
"... In PAGE 6: ... For the largest graph, the fixed simulation time was not long enough to make much improvement, but the best result occurred for , where the simulations are less fre- quent. Table2 summarizes the power reduction for the genetic algorithm with and without using the period graph, with a fixed compile time of one hour. 9 Conclusion This paper has explored a period graph model that enables efficient voltage scaling optimization for self-timed implementations of iterative applications.... ..."

Table 5.12: Genetic algorithm optimized lumber defect classifier results.

in Towards a Versatile System for the Visual Recognition of Surface Defects
by Miroslav Koprnicky 2005

Table 2: Simulated annealing amp; genetic algorithm--constrained optimization

in COMPARISON OF SIMULATED ANNEALING AND GENETIC ALGORITHM APPROACHES IN OPTIMIZING THE OUTPUT OF BIOLOGICAL PATHWAYS
by Rajesh Krishnan, Carla C. Purdy
"... In PAGE 4: ... The confidence intervals for 95% confidence level were calculated for both the algorithms. Table2... ..."

Table I. Candidate Optimization Phases in the Genetic Algorithm with Their Designations Optimization Phase Gene Description

in Fast and efficient searches for effective optimization-phase sequences
by Prasad A. Kulkarni, Stephen R. Hines, David B. Whalley, Jason D. Hiser, Jack W. Davidson, Douglas L. Jones
Cited by 7

Table 8.2. Candidate Optimization Phases in the Genetic Algorithm Experiments Optimization Phase Description

in REDUCING THE WCET OF APPLICATIONS ON LOW END EMBEDDED SYSTEMS By
by Wankang Zhao, Van Engelen, Kyle Gallivan 2005

Table 1. Optimization parameters for genetic algorithm.

in Atmospheric Chemistry and Physics Optimizing CO2 observing networks in the presence of model error:
by Results From Transcom, P. J Rayner 2004

Table 8.5. Comparison of Three Di erent Fitness Values for the Genetic Algorithm optimizing for WCET Only Code Size Only both

in REDUCING THE WCET OF APPLICATIONS ON LOW END EMBEDDED SYSTEMS By
by Wankang Zhao, Van Engelen, Kyle Gallivan 2005

Table II. Candidate Optimization Phases in the Genetic Algorithm along with their Designations Optimization Phase Gene Description

in Vista: Vpo interactive system for tuning applications
by Prasad Kulkarni, Wankang Zhao, Stephen Hines, David Whalley, Xin Yuan, Robert Van Engelen, Kyle Gallivan, Jason Hiser, Jack Davidson, Baosheng Cai, Mark Bailey 2005
Cited by 3
Results 1 - 10 of 66,925