Research on Ant Colony Algorithm Optimization Neural Network Weights Blind Equalization Algorithm
Yanxiang Geng, Liyi Zhang, Yunshan Sun, Yao Zhang, Nan Yang, Jiawei Wu · International Journal of Security and Its Applications · 2016
The project of ant colony algorithm optimization neural network combining blind equalization algorithm is proposed.The better initial weights of neural networks are provided because of the randomness, ergodicity and positive feedback of the ant colony algorithm.And then, a combination of optimal weights are found through BP algorithm, which is fast local search speed.Thus blind equalization performance is improved.Computer simulation show that, the novel blind equalization algorithm speeds up the convergence rate, reduces the remaining steady-state error and bit error rate, which is compared with the Neural Network Blind Equalization Algorithm(NNBE) and Genetic Algorithm optimization Neural Network Blind Equalization Algorithm(GA-NNBE) .