In this paper, we examine neural network equalization in a perpendicular magnetic recording channel with jitter medium noise and MR nonlinear distortion. First, we propose simplifying a neural network equalizer by using a hybrid genetic algorithm. Next, we determine the bit error rate of a PR2ML method provided with the simplified neural network equalizer and compare it to those of a conventional neural network equalizer and a transversal filter equalizer. The results were improvements of about 0.8 and 2.0 dB in the SNR of the PR2ML method using the simplified neural network equalizer compared to the conventional neural network equalizer and the transversal filter equalizer, respectively.
|ジャーナル||Electronics and Communications in Japan, Part II: Electronics (English translation of Denshi Tsushin Gakkai Ronbunshi)|
|出版ステータス||Published - 2006 2 1|
ASJC Scopus subject areas
- コンピュータ ネットワークおよび通信