{"title":"Discrete signals: sampling, quantization and coding","authors":"Max A. Little","doi":"10.1093/oso/9780198714934.003.0008","DOIUrl":null,"url":null,"abstract":"Digital signal processing and machine learning require digital data which can be processed by algorithms on computer. However, most of the real-world signals that we observe are real numbers, occurring at real time values. This means that it is impossible in practice to store these signals on a computer and we must find some approximate signal representation which is amenable to finite, digital storage. This chapter describes the main methods which are used in practice to solve this representation problem.","PeriodicalId":73290,"journal":{"name":"IEEE International Workshop on Machine Learning for Signal Processing : [proceedings]. IEEE International Workshop on Machine Learning for Signal Processing","volume":"19 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Workshop on Machine Learning for Signal Processing : [proceedings]. IEEE International Workshop on Machine Learning for Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/oso/9780198714934.003.0008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

Digital signal processing and machine learning require digital data which can be processed by algorithms on computer. However, most of the real-world signals that we observe are real numbers, occurring at real time values. This means that it is impossible in practice to store these signals on a computer and we must find some approximate signal representation which is amenable to finite, digital storage. This chapter describes the main methods which are used in practice to solve this representation problem.
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离散信号:采样、量化和编码
数字信号处理和机器学习需要数字数据,这些数据可以在计算机上通过算法进行处理。然而,我们观察到的大多数现实世界信号都是实数,以实时值出现。这意味着在实际中不可能将这些信号存储在计算机上,我们必须找到一些近似的信号表示,以适应有限的数字存储。本章描述了在实践中用来解决这个表示问题的主要方法。
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