Jean Simatic, L. Fesquet, Brigitte Bidégaray-Fesquet
{"title":"Correctly sizing FIR filter architecture in the framework of non-uniform sampling","authors":"Jean Simatic, L. Fesquet, Brigitte Bidégaray-Fesquet","doi":"10.1109/SAMPTA.2015.7148894","DOIUrl":null,"url":null,"abstract":"Based on non-uniform sampling techniques and event-driven logic, signal processing is evolving to integrate new demands such as power consumption. As power is mainly connected to the processing activity and data volume, the level-crossing sampling scheme offers a simple way to reduce data volume and consequently processing activity. Nevertheless, these good properties could be constraining for the designers because of the non-predictable sample number that can be involved in the processing. In this paper, we target a FIR filter architecture and show how to correctly size its input shift-register. This paper shows a strategy to choose the shift-register depth but also a way to dynamically adapt the computation to an heterogeneous data flow.","PeriodicalId":311830,"journal":{"name":"2015 International Conference on Sampling Theory and Applications (SampTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Sampling Theory and Applications (SampTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMPTA.2015.7148894","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
Based on non-uniform sampling techniques and event-driven logic, signal processing is evolving to integrate new demands such as power consumption. As power is mainly connected to the processing activity and data volume, the level-crossing sampling scheme offers a simple way to reduce data volume and consequently processing activity. Nevertheless, these good properties could be constraining for the designers because of the non-predictable sample number that can be involved in the processing. In this paper, we target a FIR filter architecture and show how to correctly size its input shift-register. This paper shows a strategy to choose the shift-register depth but also a way to dynamically adapt the computation to an heterogeneous data flow.