Hardware realization of higher-order CMAC model for color calibration

Jar Shone Ker, Yau Hwang Kuo, Bin Da Liu

研究成果: Paper同行評審

10 引文 斯高帕斯(Scopus)

摘要

The process of eliminating color errors from the gamut mismatch, resolution conversion, quantization and non-linearity between scanner and printer is usually recognized as an essential issue of color reproduction. To efficiently calibrate the non-linearity between scanning/printing devices, we present a linear systolic array architecture to realize the higher-order CMAC neural network model and propose an extended direct weight cell address mapping scheme for weight retrieving. This mapping scheme exhibits fast computation speed in generating weight cell addresses. Some experiments are performed to evaluate the approximation capability of the higher-order CMAC neural network models. It is shown that the CMAC model behaves well for those trained regions over the input space and exhibits smooth approximation for those untrained regions over the input space.

原文English
頁面1656-1661
頁數6
出版狀態Published - 1995
事件Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) - Perth, Aust
持續時間: 1995 11月 271995 12月 1

Other

OtherProceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6)
城市Perth, Aust
期間95-11-2795-12-01

All Science Journal Classification (ASJC) codes

  • 軟體

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