{"title":"一些低功耗DSP算法的实现","authors":"Joseph B. Evans, Bede Liu","doi":"10.1109/ASAP.1992.218566","DOIUrl":null,"url":null,"abstract":"The implementation of digital signal processing algorithms often requires that a variety of conflicting criteria be satisfied. A signal processing system must provide the necessary processing gains, while various measures of the feasibility and efficiency of implementation, such as power and cost, are met. This paper reviews the motivation behind the development of low power signal processing algorithms, presents some methods for addressing these problems, and gives several examples of reduced complexity signal processing implementations.<<ETX>>","PeriodicalId":265438,"journal":{"name":"[1992] Proceedings of the International Conference on Application Specific Array Processors","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Some low power implementations of DSP algorithms\",\"authors\":\"Joseph B. Evans, Bede Liu\",\"doi\":\"10.1109/ASAP.1992.218566\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The implementation of digital signal processing algorithms often requires that a variety of conflicting criteria be satisfied. A signal processing system must provide the necessary processing gains, while various measures of the feasibility and efficiency of implementation, such as power and cost, are met. This paper reviews the motivation behind the development of low power signal processing algorithms, presents some methods for addressing these problems, and gives several examples of reduced complexity signal processing implementations.<<ETX>>\",\"PeriodicalId\":265438,\"journal\":{\"name\":\"[1992] Proceedings of the International Conference on Application Specific Array Processors\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1992] Proceedings of the International Conference on Application Specific Array Processors\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASAP.1992.218566\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1992] Proceedings of the International Conference on Application Specific Array Processors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASAP.1992.218566","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The implementation of digital signal processing algorithms often requires that a variety of conflicting criteria be satisfied. A signal processing system must provide the necessary processing gains, while various measures of the feasibility and efficiency of implementation, such as power and cost, are met. This paper reviews the motivation behind the development of low power signal processing algorithms, presents some methods for addressing these problems, and gives several examples of reduced complexity signal processing implementations.<>
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