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CEC
2005
IEEE
15 years 8 months ago
A population-based, steady-state procedure for real-parameter optimization
Despite the existence of a number of procedures for real-parameter optimization using evolutionary algorithms, there is still a need of a systematic and unbiased comparison of diļ...
Ankur Sinha, Santosh Tiwari, Kalyanmoy Deb
DFT
2009
IEEE
210views VLSI» more  DFT 2009»
15 years 6 months ago
Optimizing Parametric BIST Using Bio-inspired Computing Algorithms
Optimizing the BIST configuration based on the characteristics of the design under test is a complicated and challenging work for test engineers. Since this problem has multiple o...
Nastaran Nemati, Amirhossein Simjour, Amirali Ghof...
TFS
2008
157views more  TFS 2008»
15 years 2 months ago
Efficient Self-Evolving Evolutionary Learning for Neurofuzzy Inference Systems
Abstract--This study proposes an efficient self-evolving evolutionary learning algorithm (SEELA) for neurofuzzy inference systems (NFISs). The major feature of the proposed SEELA i...
Cheng-Jian Lin, Cheng-Hung Chen, Chin-Teng Lin
EUROGP
2001
Springer
124views Optimization» more  EUROGP 2001»
15 years 7 months ago
An Evolutionary Approach to Automatic Generation of VHDL Code for Low-Power Digital Filters
An evolutionary algorithm is used to design a finite impulse response digital filter with reduced power consumption. The proposed design approach combines genetic optimization an...
Massimiliano Erba, Roberto Rossi, Valentino Libera...
AEI
2005
99views more  AEI 2005»
15 years 3 months ago
Comparison among five evolutionary-based optimization algorithms
Evolutionary algorithms (EAs) are stochastic search methods that mimic the natural biological evolution and/or the social behavior of species. Such algorithms have been developed ...
Emad Elbeltagi, Tarek Hegazy, Donald E. Grierson