Adaptiver comb-filtering using neural networks

Prange, Jansen, Horn
{"title":"Adaptiver comb-filtering using neural networks","authors":"Prange, Jansen, Horn","doi":"10.1109/30.628727","DOIUrl":null,"url":null,"abstract":"Neural networks of multi-layer perceptron type perform well as adaptive comb-filters for PAL and NTSC color decoding. They are optimized by learning algorithms. Sampled encoded and original images serve as training patterns.","PeriodicalId":127085,"journal":{"name":"1997 International Conference on Consumer Electronics","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1997 International Conference on Consumer Electronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/30.628727","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Neural networks of multi-layer perceptron type perform well as adaptive comb-filters for PAL and NTSC color decoding. They are optimized by learning algorithms. Sampled encoded and original images serve as training patterns.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于神经网络的自适应梳状滤波
多层感知器类型的神经网络作为自适应梳状滤波器在PAL和NTSC颜色解码中表现良好。它们是通过学习算法优化的。采样编码和原始图像作为训练模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Display Processor Conforming To All ATV Formats With 188-tap FIR Filters And 284 Kb FIFO Memories Design And Implementation Of Internet-tv Development Of A New Television Set With Personal Computer Capability Video Compression With Custom Computers A New Family Of Zero Voltage Switching Power Supplies
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1