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In [3], Poonen and Slavov recently developed a novel approach to Bertini irreducibility theorems over an arbitrary field, based on random hyperplane slicing. In this paper, we extend their work by proving an analogous bound for the dimension of the exceptional locus in the setting of linear subspaces of higher codimensions. 相似文献
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Abstract A comparison and evaluation is made of recent proposals for multivariate matched sampling in observational studies, where the following three questions are answered: (1) Algorithms: In current statistical practice, matched samples are formed using “nearest available” matching, a greedy algorithm. Greedy matching does not minimize the total distance within matched pairs, though good algorithms exist for optimal matching that do minimize the total distance. How much better is optimal matching than greedy matching? We find that optimal matching is sometimes noticeably better than greedy matching in the sense of producing closely matched pairs, sometimes only marginally better, but it is no better than greedy matching in the sense of producing balanced matched samples. (2) Structures: In common practice, treated units are matched to one control, called pair matching or 1–1 matching, or treated units are matched to two controls, called 1–2 matching, and so on. It is known, however, that the optimal structure is a full matching in which a treated unit may have one or more controls or a control may have one or more treated units. Optimal 1 — k matching is compared to optimal full matching, finding that optimal full matching is often much better. (3) Distances: Matching involves defining a distance between covariate vectors, and several such distances exist. Three recent proposals are compared. Practical advice is summarized in a final section. 相似文献
95.
S. Huzurbazar Ronald W. Butler 《Journal of computational and graphical statistics》2013,22(3):342-355
Abstract An importance sampling procedure is developed to approximate the distribution of an arbitrary function of the eigenvalues for a matrix beta random matrix or a Wishart random matrix. The procedure is easily implemented and provides confidence intervals for the p-values of many of the commonly used test statistics in multivariate analysis. An adaptive procedure allows for the control of either absolute error or relative error in this p-value estimation through the choice of importance sample size. 相似文献
96.
Abstract Algorithms are developed for constructing random variable generators for families of densities. The generators depend on the concavity structure of a transformation of the density. The resulting algorithms are rejection algorithms and the methods of this article are concerned with constructing good rejection algorithms for general densities. 相似文献
97.
Solid phase microextraction (SPME), a simple, fast and promising sampling technique, has been widely used for complex sample analysis. However, complex matrices could modify the absorption property of coatings as well as the uptake kinetics of analytes, eventually biasing the quantification results. In the current study, we demonstrated the feasibility of a developed calibration method for the analysis of polycyclic aromatic hydrocarbons (PAHs) in complex milk samples. Effects of the complex matrices on the SPME sampling process and the sampling conditions were investigated. Results showed that short exposure time (pre-equilibrium SPME, PE-SPME) could increase the lifetime of coatings, and the complex matrices in milk samples could significantly influence the sampling kinetics of SPME. In addition, the optimized sampling time, temperature and dilution factor for PAHs were 10 min, 85 °C and 20, respectively. The obtained LODs and LOQs of all the PAHs were 0.1–0.8 ng/mL and 1.4–4.7 ng/mL, respectively. Furthermore, the accuracy of the proposed PE-SPME method for milk sampling was validated by the recoveries of the studied compounds in two concentration levels, which ranged from 75% to 110% for all the compounds. Finally, the proposed method was applied to the screening of PAHs in milk samples. 相似文献
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Pierre Del Moral 《随机分析与应用》2018,36(3):413-442
In this article, we consider importance sampling (IS) and sequential Monte Carlo (SMC) methods in the context of one-dimensional random walks with absorbing barriers. In particular, we develop a very precise variance analysis for several IS and SMC procedures. We take advantage of some explicit spectral formulae available for these models to derive sharp and explicit estimates; this provides stability properties of the associated normalized Feynman–Kac semigroups. Our analysis allows one to compare the variance of SMC and IS techniques for these models. The work in this article is one of the few to consider an in-depth analysis of an SMC method for a particular model-type as well as variance comparison of SMC algorithms. 相似文献
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