@article{(Open Science Index):https://publications.waset.org/pdf/12622,
	  title     = {Classification of Initial Stripe Height Patterns using Radial Basis Function Neural Network for Proportional Gain Prediction},
	  author    = {Prasit Wonglersak and  Prakarnkiat Youngkong and  Ittipon Cheowanish},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper aims to improve a fine lapping process of
hard disk drive (HDD) lapping machines by removing materials from
each slider together with controlling the strip height (SH) variation to
minimum value. The standard deviation is the key parameter to
evaluate the strip height variation, hence it is minimized. In this
paper, a design of experiment (DOE) with factorial analysis by twoway
analysis of variance (ANOVA) is adopted to obtain a
statistically information. The statistics results reveal that initial stripe
height patterns affect the final SH variation. Therefore, initial SH
classification using a radial basis function neural network is
implemented to achieve the proportional gain prediction.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {5},
	  number    = {4},
	  year      = {2011},
	  pages     = {377 - 379},
	  ee        = {https://publications.waset.org/pdf/12622},
	  url   	= {https://publications.waset.org/vol/52},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 52, 2011},