This paper describes the implementation of a genetic algorithm to evolve the population of weight matrices for storing and recalling the patterns in a Hopfield type neural network model. In the Hopfield type neural network of associative memory, the appropriate arrangement of synaptic weights provid
β¦ LIBER β¦
A software pattern of the Genetic Algorithm
β Scribed by Zhuo Shi; Liu Chao; He Ke-qing
- Book ID
- 105718521
- Publisher
- Wuhan University
- Year
- 2001
- Tongue
- English
- Weight
- 647 KB
- Volume
- 6
- Category
- Article
- ISSN
- 1007-1202
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Pattern recall analysis of the Hopfield
β
Somesh Kumar; Manu Pratap Singh
π
Article
π
2010
π
Elsevier Science
π
English
β 303 KB
Low-sidelobe pattern synthesis of spheri
β
You Chung Chung; Randy Haupt
π
Article
π
2002
π
John Wiley and Sons
π
English
β 132 KB
## Abstract A genetic algorithm (GA) finds complex weights that yield lowβsidelobe levels for spherical arrays. The first example is a sphericalβplanar array with an initial high sidelobe of β13 dB, and which has an optimized pattern with a maximum sidelobe level of β27 dB. The second example is a
Array pattern nulling by element positio
β
Tennant, A.; Dawoud, M.M.; Anderson, A.P.
π
Article
π
1994
π
The Institution of Electrical Engineers
π
English
β 280 KB
The optimization of success probability
β
Francisco Reyes; Narciso Cerpa; Alfredo Candia-VΓ©jar; Matthew Bardeen
π
Article
π
2011
π
Elsevier Science
π
English
β 552 KB
The Proportional Genetic Algorithm: Gene
β
Annie S. Wu; Ivan Garibay
π
Article
π
2002
π
Springer
π
English
β 343 KB
Generation of jumping motion pattern for
β
Yoshiro Yoshida; Takuya Kamano; Takadhi Yasuno; Yu Kataoka
π
Article
π
2000
π
Springer Japan
π
English
β 752 KB