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» Evolving Quantum Circuits Using Genetic Algorithm
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DAC
2000
ACM
16 years 3 months ago
Formal verification of iterative algorithms in microprocessors
Contemporary microprocessors implement many iterative algorithms. For example, the front-end of a microprocessor repeatedly fetches and decodes instructions while updating interna...
Mark Aagaard, Robert B. Jones, Roope Kaivola, Kath...
110
Voted
ICSEA
2007
IEEE
15 years 8 months ago
Software Environment for Research on Evolving User Interface Designs
We investigate the trade off between investing effort in improving the features of a research environment that increases productivity and investing such effort in actually conduct...
Juan C. Quiroz, Anil Shankar, Sergiu M. Dascalu, S...
IJCAI
1997
15 years 3 months ago
Evolvable Hardware for Generalized Neural Networks
This paper describes an evolvable hardware (EHW) system for generalized neural network learning. We have developed an ASIC VLSI chip, which is a building block to configure a scal...
Masahiro Murakawa, Shuji Yoshizawa, Isamu Kajitani...
SIGADA
2004
Springer
15 years 7 months ago
Comparative analysis of genetic algorithm implementations
Genetic Algorithms provide computational procedures that are modeled on natural genetic system mechanics, whereby a coded solution is “evolved” from a set of potential solutio...
Robert Soricone, Melvin Neville
GECCO
1999
Springer
133views Optimization» more  GECCO 1999»
15 years 6 months ago
Forecasting the MagnetoEncephaloGram (MEG) of Epileptic Patients Using Genetically Optimized Neural Networks
In this work MagnetoEncephaloGram (MEG) recordings of epileptic patients were analyzed using a hybrid neural networks training algorithm. This algorithm combines genetic algorithm...
Adam V. Adamopoulos, Efstratios F. Georgopoulos, S...