نتایج جستجو برای: mean kernel weight
تعداد نتایج: 943096 فیلتر نتایج به سال:
In this paper, we study the mean square convergence of the kernel least mean square (KLMS). The fundamental energy conservation relation has been established in feature space. Starting from the energy conservation relation, we carry out the mean square convergence analysis and obtain several important theoretical results, including an upper bound on step size that guarantees the mean square con...
In order to study effect of drought stress on morphologic traits, yield and yield components of 28 new hybrids of corn to heat and drought stress in addition 6 commercial hybrid (as control), an experiment was carried out on based of complete randomized block design with three replication under normal irrigation and drought stress in Khorasan Razavi Agricultural Research and Natural Resources I...
Mean shift is a popular robust framework for statistical data analysis using kernel density estimation, originally proposed by Fukunaga and Hostetler in 70’s. Recently, due to the work by Cheng and Comaniciu, this method has been re-discovered and successfully applied to a wide range of vision applications. This article provides a comprehensive overview of the basic theory and applications of m...
Drought stress is the most important limiting factor in crop plants including maize (Zea mays L.), which is the third important world crop after wheat and rice. Water deficiency at different growth stages affects maize yield differently. To examine the response of four maize hybrids to drought stress at different growth stages, a field experiment was carried out as a split plot based on complet...
On the Estimation of the Gradient Lines of a Density and the Consistency of the Mean-Shift Algorithm
We consider the problem of estimating the gradient lines of a density, which can be used to cluster points sampled from that density, for example via the mean-shift algorithm of Fukunaga and Hostetler (1975). We prove general convergence bounds that we then specialize to kernel density estimation.
To improve a complex character such as yield with low heritability, the use of indirect selection through other characters and a selection index based on different effective traits is recommended. This study was conducted to evaluate different selection methods by using 23 F2:4 wheat lines derived from the cross of Virmarin (susceptible cultivar) and Sardari (tolerant cultivar) at Research Farm...
To improve a complex character such as yield with low heritability, the use of indirect selection through other characters and a selection index based on different effective traits is recommended. This study was conducted to evaluate different selection methods by using 23 F2:4 wheat lines derived from the cross of Virmarin (susceptible cultivar) and Sardari (tolerant cultivar) at Research Farm...
One of a nonparametric procedures used to estimate densities is kernel method. In this paper, in order to reduce bias of kernel density estimation, methods such as usual kernel(UK), geometric extrapolation usual kernel(GEUK), a bias reduction kernel(BRK) and a geometric extrapolation bias reduction kernel(GEBRK) are introduced. Theoretical properties, including the selection of smoothness para...
Kernel weight is important for plant breeders to select high productive plants. The determination of relationships between kernel weight and some fruit-kernel characteristics may provide necessary information for plant breeders in selection programs. In the present study, the relationships between kernel weight (KW) and 7 fruit-kernel characteristics: Fruit Length, (FL,), Fruit Width (FW) Fruit...
The present paper is dealing with optimization problems arising in the context of kernel estimates of a density and a regression function. Kernel estimates are one of the most popular nonparametric functional estimates. These estimates depend on a bandwidth which controls the smoothness of the estimate and on a kernel which plays a role of a weight function. In this paper we concentrate on a ch...
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