非高斯时间序列的性质和生成

ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing Pub Date : 1987-04-06 DOI:10.1109/ICASSP.1987.1169624

Don H. Johnson, P. Rao

{"title":"非高斯时间序列的性质和生成","authors":"Don H. Johnson, P. Rao","doi":"10.1109/ICASSP.1987.1169624","DOIUrl":null,"url":null,"abstract":"It is shown that non-Gaussian time series require new analysis methods to extract their structure. Spectral analysis does not seem to provide the precise information required to analyze important aspects of a time series. The conditional expected value can, in simple cases, be related to Components of the Barrett-Lampard expansion, which provides a mathematical tool for determining the system which can generate the time series.","PeriodicalId":140810,"journal":{"name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1987-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Properties and generation of non-Gaussian time series\",\"authors\":\"Don H. Johnson, P. Rao\",\"doi\":\"10.1109/ICASSP.1987.1169624\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is shown that non-Gaussian time series require new analysis methods to extract their structure. Spectral analysis does not seem to provide the precise information required to analyze important aspects of a time series. The conditional expected value can, in simple cases, be related to Components of the Barrett-Lampard expansion, which provides a mathematical tool for determining the system which can generate the time series.\",\"PeriodicalId\":140810,\"journal\":{\"name\":\"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1987-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.1987.1169624\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.1987.1169624","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 6

摘要

研究表明，非高斯时间序列需要新的分析方法来提取其结构。谱分析似乎不能提供分析时间序列重要方面所需的精确信息。在简单的情况下，条件期望值可以与巴雷特-兰帕德展开的分量相关，它提供了一个数学工具来确定可以生成时间序列的系统。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Properties and generation of non-Gaussian time series

It is shown that non-Gaussian time series require new analysis methods to extract their structure. Spectral analysis does not seem to provide the precise information required to analyze important aspects of a time series. The conditional expected value can, in simple cases, be related to Components of the Barrett-Lampard expansion, which provides a mathematical tool for determining the system which can generate the time series.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing

自引率

0.00%

发文量