Interpreting self-organizing maps through space–time data models
نویسندگان
چکیده
منابع مشابه
Interpreting Self - Organizing Maps through Space – Time Data Models
Self-organizing maps (SOMs) are a technique that has been used with high-dimensional data vectors to develop an archetypal set of states (nodes) that span, in some sense, the high-dimensional space. Noteworthy applications include weather states as described by weather variables over a region and speech patterns as characterized by frequencies in time. The SOM approach is essentially a neural n...
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شبکه خود سازمانده پرکاربردترین شبکه عصبی برای انجام خوشه بندی و کوانتیزه نمودن برداری است. از زمان معرفی این شبکه تاکنون، از این روش در مسائل مختلف در حوزه های گوناگون استفاده و توسعه ها و بهبودهای متعددی برای آن ارائه شده است. شبکه خودسازمانده از تعدادی سلول برای تخمین تابع توزیع الگوهای ورودی در فضای چندبعدی استفاده می کند. احتمال وجود سلول مرده مشکلی اساسی در الگوریتم شبکه خودسازمانده به حسا...
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ژورنال
عنوان ژورنال: The Annals of Applied Statistics
سال: 2008
ISSN: 1932-6157
DOI: 10.1214/08-aoas174