標(biāo)題: Titlebook: Wavelets, Approximation, and Statistical Applications; Wolfgang H?rdle,Gerard Kerkyacharian,Alexander Tsy Book 1998 Springer-Verlag New Yo [打印本頁] 作者: Hermit 時間: 2025-3-21 18:54
書目名稱Wavelets, Approximation, and Statistical Applications影響因子(影響力)
書目名稱Wavelets, Approximation, and Statistical Applications影響因子(影響力)學(xué)科排名
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書目名稱Wavelets, Approximation, and Statistical Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Wavelets, Approximation, and Statistical Applications被引頻次
書目名稱Wavelets, Approximation, and Statistical Applications被引頻次學(xué)科排名
書目名稱Wavelets, Approximation, and Statistical Applications年度引用
書目名稱Wavelets, Approximation, and Statistical Applications年度引用學(xué)科排名
書目名稱Wavelets, Approximation, and Statistical Applications讀者反饋
書目名稱Wavelets, Approximation, and Statistical Applications讀者反饋學(xué)科排名
作者: 正論 時間: 2025-3-21 22:35 作者: 挑剔小責(zé) 時間: 2025-3-22 00:26 作者: Pessary 時間: 2025-3-22 04:46 作者: jovial 時間: 2025-3-22 10:49
The Haar basis wavelet system,The Haar basis is known since 1910. Here we consider the Haar basis on the real line . and describe some of its properties which are useful for the construction of general wavelet systems. Let . (.) be the space of all complex valued functions . on . such that their .-norm is finite:作者: Supplement 時間: 2025-3-22 13:45 作者: isotope 時間: 2025-3-22 17:27 作者: 耐寒 時間: 2025-3-22 23:59 作者: 補充 時間: 2025-3-23 02:31
Some facts from Fourier analysis,This small chapter is here to summarize the classical facts of Fourier analysis that will be used in the sequel. We omit the proofs (except for the Poisson summation formula). They can be found in standard textbooks on the subject, for instance in Katznelson (1976), Stein & Weiss (1971).作者: Nebulous 時間: 2025-3-23 06:15 作者: BRIDE 時間: 2025-3-23 12:45 作者: 箴言 時間: 2025-3-23 16:07
Basic relations of wavelet theory,Let us formulate in the exact form the conditions on the functions . and . which guarantee that the wavelet expansion (3.5) holds. This formulation is connected with the following questions.作者: 可卡 時間: 2025-3-23 20:21
Computational aspects and statistical software implementations,In this chapter we discuss how to compute the wavelet estimators and give a brief overview of the statistical wavelets software.作者: 苦笑 時間: 2025-3-24 01:32 作者: BIAS 時間: 2025-3-24 05:18
Lecture Notes in Statisticshttp://image.papertrans.cn/w/image/1021295.jpg作者: 衣服 時間: 2025-3-24 09:00 作者: SMART 時間: 2025-3-24 14:14 作者: 好忠告人 時間: 2025-3-24 18:48 作者: Culpable 時間: 2025-3-24 22:04
Construction of wavelet bases,ion .. For more details on wavelet basis construction we refer to Daubechies (1992),Chui(1992a, 1992b), Meyer (1993), Young (1993), Cohen & Ryan (1995), Holschneider (1995), Kahane & Lemarié-Rieusset (1995), Kaiser (1995).作者: 雀斑 時間: 2025-3-25 01:09
Construction of wavelet bases,ion .. For more details on wavelet basis construction we refer to Daubechies (1992),Chui(1992a, 1992b), Meyer (1993), Young (1993), Cohen & Ryan (1995), Holschneider (1995), Kahane & Lemarié-Rieusset (1995), Kaiser (1995).作者: 補角 時間: 2025-3-25 06:16
Wavelets and Besov Spaces,. The results of Chapter 8 are substantially used throughout. General references about Besov spaces are Nikol‘skii (1975), Peetre (1975), Besov, Il‘in & Nikol‘skii (1978), Bergh & L?fstr?m (1976), Triebel (1992), DeVore & Lorentz (1993).作者: Concrete 時間: 2025-3-25 07:55 作者: 下級 時間: 2025-3-25 14:38 作者: 摘要 時間: 2025-3-25 19:03
Wavelets, followed by lower frequency waves or vice versa. The theory of wavelet reconstruction helps to localize and identify such accumulations of small waves and helps thus to better understand reasons for these phenomena. Wavelet theory is different from Fourier analysis and spectral theory since it is b作者: linear 時間: 2025-3-25 21:24
Wavelets, followed by lower frequency waves or vice versa. The theory of wavelet reconstruction helps to localize and identify such accumulations of small waves and helps thus to better understand reasons for these phenomena. Wavelet theory is different from Fourier analysis and spectral theory since it is b作者: 火車車輪 時間: 2025-3-26 00:44 作者: 盟軍 時間: 2025-3-26 05:15 作者: 清唱劇 時間: 2025-3-26 11:27
Compactly supported wavelets,terested to find the exact form of functions .(.), which are trigonometric polynomials, and produce father .and mother .with compact supports such that, in addition, the moments of . and . of order from 1 to n vanish. This property is necessary to guarantee good approximation properties of the corre作者: 頑固 時間: 2025-3-26 15:03
Compactly supported wavelets,terested to find the exact form of functions .(.), which are trigonometric polynomials, and produce father .and mother .with compact supports such that, in addition, the moments of . and . of order from 1 to n vanish. This property is necessary to guarantee good approximation properties of the corre作者: galley 時間: 2025-3-26 16:57 作者: Boycott 時間: 2025-3-26 22:15 作者: immunity 時間: 2025-3-27 03:09 作者: 乞丐 時間: 2025-3-27 05:40
Wavelets and Besov Spaces,ch more general tool in describing the smoothness properties of functions. We show that Besov spaces admit a characterization in terms of wavelet coefficients, which is not the case for Sobolev spaces. Thus the Besov spaces are intrinsically connected to the analysis of curves via wavelet techniques作者: 完成 時間: 2025-3-27 12:24 作者: 催眠 時間: 2025-3-27 14:36 作者: 冥界三河 時間: 2025-3-27 19:46
Wavelet thresholding and adaptation,d generalizations of soft and hard thresholding. Then we develop the notion of adaptive estimators and present the results about adaptivity of wavelet thresholding for density estimation problems. Finally, we consider the data-driven methods of selecting the wavelet basis, the threshold value and th作者: Nonflammable 時間: 2025-3-27 23:49 作者: 憤慨點吧 時間: 2025-3-28 03:51 作者: 無法解釋 時間: 2025-3-28 06:34
Wavelets and Approximation,v spaces and show that it has an intrinsic relation to wavelet expansions. The presentation in this chapter and in Chapter 9 is more formal than in the previous ones. It is designed for the mathematically oriented reader who is interested in a deeper theoretical insight into the properties of wavelet bases.作者: Forage飼料 時間: 2025-3-28 12:56
Wavelets and Approximation,v spaces and show that it has an intrinsic relation to wavelet expansions. The presentation in this chapter and in Chapter 9 is more formal than in the previous ones. It is designed for the mathematically oriented reader who is interested in a deeper theoretical insight into the properties of wavelet bases.作者: 報復(fù) 時間: 2025-3-28 17:23
Statistical estimation using wavelets,proximation is both in frequency and space. In this chapter we consider the problem of nonparametric statistical estimation of a function . in .(.) by wavelet methods. We study the density estimation and nonparametric regression settings. We also present empirical results of wavelet smoothing.作者: BYRE 時間: 2025-3-28 22:11 作者: nuclear-tests 時間: 2025-3-29 01:08 作者: heckle 時間: 2025-3-29 06:39
Wavelet thresholding and adaptation, thresholding for density estimation problems. Finally, we consider the data-driven methods of selecting the wavelet basis, the threshold value and the initial resolution level, based on Stein’s principle. We finish by a discussion of oracle inequalities and miscellaneous related topics.作者: Projection 時間: 2025-3-29 08:13
Wolfgang H?rdle,Gerard Kerkyacharian,Dominique Picard,Alexander Tsybakov作者: EXALT 時間: 2025-3-29 11:46 作者: Vital-Signs 時間: 2025-3-29 18:32
Wolfgang H?rdle,Gerard Kerkyacharian,Dominique Picard,Alexander Tsybakov作者: ostracize 時間: 2025-3-29 21:09
Wolfgang H?rdle,Gerard Kerkyacharian,Dominique Picard,Alexander Tsybakov作者: 天賦 時間: 2025-3-30 02:46 作者: 粗野 時間: 2025-3-30 05:35 作者: 杠桿支點 時間: 2025-3-30 09:18
Wolfgang H?rdle,Gerard Kerkyacharian,Dominique Picard,Alexander Tsybakov作者: 未成熟 時間: 2025-3-30 16:13
Wolfgang H?rdle,Gerard Kerkyacharian,Dominique Picard,Alexander Tsybakov作者: Digest 時間: 2025-3-30 18:27
Wolfgang H?rdle,Gerard Kerkyacharian,Dominique Picard,Alexander Tsybakov作者: 上下連貫 時間: 2025-3-30 22:38
Wolfgang H?rdle,Gerard Kerkyacharian,Dominique Picard,Alexander Tsybakov作者: 身體萌芽 時間: 2025-3-31 01:16
Wolfgang H?rdle,Gerard Kerkyacharian,Dominique Picard,Alexander Tsybakov作者: Muffle 時間: 2025-3-31 06:44 作者: 懸掛 時間: 2025-3-31 11:36 作者: 苦笑 時間: 2025-3-31 17:15
Wolfgang H?rdle,Gerard Kerkyacharian,Dominique Picard,Alexander Tsybakov作者: 因無茶而冷淡 時間: 2025-3-31 19:37 作者: 排出 時間: 2025-3-31 21:59
Wolfgang H?rdle,Gerard Kerkyacharian,Dominique Picard,Alexander Tsybakov作者: 貧窮地活 時間: 2025-4-1 02:31 作者: Eructation 時間: 2025-4-1 06:30
Wavelets, Approximation, and Statistical Applications作者: 自然環(huán)境 時間: 2025-4-1 11:40
Wolfgang H?rdle,Gerard Kerkyacharian,Alexander Tsy作者: 昆蟲 時間: 2025-4-1 14:46 作者: insincerity 時間: 2025-4-1 19:53
Wolfgang H?rdle,Gerard Kerkyacharian,Dominique Picard,Alexander Tsybakovcance and the?impacts of both reputation and social relationship of smartphone users?(SUs) in MCS and presents extensive simulation results to demonstrate the g978-3-030-01023-2978-3-030-01024-9Series ISSN 2191-8112 Series E-ISSN 2191-8120 作者: Endoscope 時間: 2025-4-2 02:37
Wolfgang H?rdle,Gerard Kerkyacharian,Dominique Picard,Alexander Tsybakovors provide existing personalized?treatments for mobile applications, as the behaviors may differ greatly from?one user to another in many mobile applications. 978-3-030-02100-9978-3-030-02101-6Series ISSN 2191-5768 Series E-ISSN 2191-5776 作者: 大暴雨 時間: 2025-4-2 05:11 作者: orient 時間: 2025-4-2 08:37
ht sowie die vielf?ltigen Vertriebsimplikationen auf der Bankseite. Abschlie?end erfolgt eine praxisnahe Verifizierung der gewonnenen Erkenntnisse durch eine repr?sentative Expertenbefragung..978-3-8244-8134-7978-3-322-81778-5Series ISSN 2627-6364 Series E-ISSN 2627-6372
