找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Robustness in Statistical Pattern Recognition; Yurij Kharin Book 1996 Springer Science+Business Media Dordrecht 1996 classification.cluste

[復(fù)制鏈接]
查看: 6459|回復(fù): 37
樓主
發(fā)表于 2025-3-21 18:44:52 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Robustness in Statistical Pattern Recognition
編輯Yurij Kharin
視頻videohttp://file.papertrans.cn/832/831406/831406.mp4
叢書名稱Mathematics and Its Applications
圖書封面Titlebook: Robustness in Statistical Pattern Recognition;  Yurij Kharin Book 1996 Springer Science+Business Media Dordrecht 1996 classification.cluste
描述This book is concerned with important problems of robust (stable) statistical pat- tern recognition when hypothetical model assumptions about experimental data are violated (disturbed). Pattern recognition theory is the field of applied mathematics in which prin- ciples and methods are constructed for classification and identification of objects, phenomena, processes, situations, and signals, i. e. , of objects that can be specified by a finite set of features, or properties characterizing the objects (Mathematical Encyclopedia (1984)). Two stages in development of the mathematical theory of pattern recognition may be observed. At the first stage, until the middle of the 1970s, pattern recogni- tion theory was replenished mainly from adjacent mathematical disciplines: mathe- matical statistics, functional analysis, discrete mathematics, and information theory. This development stage is characterized by successful solution of pattern recognition problems of different physical nature, but of the simplest form in the sense of used mathematical models. One of the main approaches to solve pattern recognition problems is the statisti- cal approach, which uses stochastic models of feature
出版日期Book 1996
關(guān)鍵詞classification; cluster analysis; cognition; control; cybernetics; mathematics; modeling; pattern recogniti
版次1
doihttps://doi.org/10.1007/978-94-015-8630-6
isbn_softcover978-90-481-4760-1
isbn_ebook978-94-015-8630-6
copyrightSpringer Science+Business Media Dordrecht 1996
The information of publication is updating

書目名稱Robustness in Statistical Pattern Recognition影響因子(影響力)




書目名稱Robustness in Statistical Pattern Recognition影響因子(影響力)學(xué)科排名




書目名稱Robustness in Statistical Pattern Recognition網(wǎng)絡(luò)公開(kāi)度




書目名稱Robustness in Statistical Pattern Recognition網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書目名稱Robustness in Statistical Pattern Recognition被引頻次




書目名稱Robustness in Statistical Pattern Recognition被引頻次學(xué)科排名




書目名稱Robustness in Statistical Pattern Recognition年度引用




書目名稱Robustness in Statistical Pattern Recognition年度引用學(xué)科排名




書目名稱Robustness in Statistical Pattern Recognition讀者反饋




書目名稱Robustness in Statistical Pattern Recognition讀者反饋學(xué)科排名




單選投票, 共有 1 人參與投票
 

0票 0.00%

Perfect with Aesthetics

 

1票 100.00%

Better Implies Difficulty

 

0票 0.00%

Good and Satisfactory

 

0票 0.00%

Adverse Performance

 

0票 0.00%

Disdainful Garbage

您所在的用戶組沒(méi)有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 21:51:44 | 只看該作者
板凳
發(fā)表于 2025-3-22 02:10:16 | 只看該作者
https://doi.org/10.1007/978-94-015-8630-6classification; cluster analysis; cognition; control; cybernetics; mathematics; modeling; pattern recogniti
地板
發(fā)表于 2025-3-22 07:49:11 | 只看該作者
Probability Models of Data and Optimal Decision Rules,lds, and random sets. Optimal (Bayesian) decision rules minimizing the classification risk are specified. These decision rules are defined in discrete and continuous spaces of feature variables. The computational formulae for risk are given.
5#
發(fā)表于 2025-3-22 12:10:26 | 只看該作者
Robustness of Nonparametric Decision Rules and Small-sample Effects,nonparametric decision rules (Rosenblatt-Parzen, .-nearest neighbor) are used for classification. We find optimal values for smoothness parameters that optimize the robustness factor. We compare stability of parametric and nonparametric decision rules.
6#
發(fā)表于 2025-3-22 14:43:42 | 只看該作者
Book 1996haracterized by successful solution of pattern recognition problems of different physical nature, but of the simplest form in the sense of used mathematical models. One of the main approaches to solve pattern recognition problems is the statisti- cal approach, which uses stochastic models of feature
7#
發(fā)表于 2025-3-22 19:08:00 | 只看該作者
stage is characterized by successful solution of pattern recognition problems of different physical nature, but of the simplest form in the sense of used mathematical models. One of the main approaches to solve pattern recognition problems is the statisti- cal approach, which uses stochastic models of feature978-90-481-4760-1978-94-015-8630-6
8#
發(fā)表于 2025-3-22 22:25:18 | 只看該作者
9#
發(fā)表于 2025-3-23 02:07:33 | 只看該作者
10#
發(fā)表于 2025-3-23 07:44:40 | 只看該作者
Yurij Kharinterdisziplin?ren Zugang charakterisiert, der eine Vielzahl human-, geistes-, kultur- und sozialwissenschaftlicher Perspektiven bündelt. Aktuelle, fundierte und von ausgewiesenen Fachleuten verfasste Beitr?ge geben einen überblick über Themenfelder und Debatten der Menschenbildforschung und arbeiten
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-7 04:59
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
乡城县| 惠安县| 珲春市| 大名县| 务川| 乌兰县| 浦江县| 凌海市| 合江县| 平陆县| 平潭县| 香格里拉县| 内丘县| 东明县| 三门峡市| 都昌县| 搜索| 容城县| 建始县| 奉化市| 南溪县| 社旗县| 九台市| 阿城市| 东方市| 竹溪县| 交城县| 烟台市| 九寨沟县| 天峨县| 府谷县| 丹寨县| 甘孜县| 图们市| 阳西县| 霍林郭勒市| 柯坪县| 繁昌县| 湖北省| 崇义县| 南丰县|