随机非线性动力学模式形成和增长模型。

Nonlinear biomedical physics Pub Date : 2007-07-05 DOI:10.1186/1753-4631-1-4

Leonid P Yaroslavsky

{"title":"随机非线性动力学模式形成和增长模型。","authors":"Leonid P Yaroslavsky","doi":"10.1186/1753-4631-1-4","DOIUrl":null,"url":null,"abstract":" Stochastic evolutionary growth and pattern formation models are treated in a unified way in terms of algorithmic models of nonlinear dynamic systems with feedback built of a standard set of signal processing units. A number of concrete models is described and illustrated by numerous examples of artificially generated patterns that closely imitate wide variety of patterns found in the nature.","PeriodicalId":87480,"journal":{"name":"Nonlinear biomedical physics","volume":"1 1","pages":"4"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/1753-4631-1-4","citationCount":"6","resultStr":"{\"title\":\"Stochastic nonlinear dynamics pattern formation and growth models.\",\"authors\":\"Leonid P Yaroslavsky\",\"doi\":\"10.1186/1753-4631-1-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\" Stochastic evolutionary growth and pattern formation models are treated in a unified way in terms of algorithmic models of nonlinear dynamic systems with feedback built of a standard set of signal processing units. A number of concrete models is described and illustrated by numerous examples of artificially generated patterns that closely imitate wide variety of patterns found in the nature.\",\"PeriodicalId\":87480,\"journal\":{\"name\":\"Nonlinear biomedical physics\",\"volume\":\"1 1\",\"pages\":\"4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1186/1753-4631-1-4\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nonlinear biomedical physics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/1753-4631-1-4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nonlinear biomedical physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/1753-4631-1-4","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

随机进化增长模型和模式形成模型统一地用一组标准信号处理单元建立的具有反馈的非线性动态系统的算法模型来处理。许多具体的模型被描述并通过许多人工生成的模式的例子来说明，这些模式密切模仿自然界中发现的各种模式。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

摘要图片

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Stochastic nonlinear dynamics pattern formation and growth models.

Stochastic evolutionary growth and pattern formation models are treated in a unified way in terms of algorithmic models of nonlinear dynamic systems with feedback built of a standard set of signal processing units. A number of concrete models is described and illustrated by numerous examples of artificially generated patterns that closely imitate wide variety of patterns found in the nature.

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

Nonlinear biomedical physics

自引率

0.00%

发文量