查询词典 kernel

By comparing the activity of theα-amylase and the soluble acid invertase in the kernel and the pedicel, the trend of theα-amylase activity in the kernel and the pedicel showed a peak, theα-amylase activity was high in the early stage, it could promoted amylolysis, supply the nutrition for the kernel development; theα-amylase activity was low in the rapid filling stage, it was in favorable to the starch accumulation.

通过比较籽粒和小穗柄中α-淀粉酶和可溶性酸性蔗糖转化酶的活性表明，籽粒和小穗柄中α-淀粉酶活性均呈单峰变化趋势，籽粒发育早期α-淀粉酶活性较高，可以促使淀粉转化，为籽粒的早期的发育提供营养物质；籽粒发育中期为快速灌浆期，淀粉酶活性较低，利于淀粉的积累。

Algorithm application of neural networks.Ⅲ Implementation of neuro-computers. The main contribution of the dissertation can be summarized as follows: 1 Hopf bifurcation of three kind of neural networks are discussed in detail, including type of discrete time delay, type of time delay with weak kernel and strong kernel as well as the proof of existence of bifurcation. Other problems such as asymptotic stability of bifurcation periodic solution, algorithm of determining the bifurcation direction, asymptotic stability and style of periodic solution are also studied. The average time delay is chosen as the bifurcation parameter, phenomena pertinent to system states of the continuous time delay network with strong kernel evolving from stable to oscillating, then back to stable again are observed.

论文的主要创新之处可以归纳如下： 1）针对目前国内外对神经网络的分岔研究较少的情况，论文中详细讨论了带离散时延神经网络、带弱核的连续时延神经网络、带连续分布时延且具有强核的神经网络的Hopf分岔现象，从理论上证明了Hopf分岔的存在性，并研究了分岔周期解的渐近稳定性，得到了确定周期解的渐近稳定性、分岔方向、周期解的渐近形式的算法；用平均时延作为分岔参数，发现带强核的连续时延神经网络中存在着系统的状态由稳定变化到振荡现象，当继续增加平均时延参数时，又从振荡变为稳定这一特殊的动力学现象。

Dorea advanced kernel estimation p of p ,which is a general density with respect to a σ-finite measure v on.ξ is a σ-field of subsets of ER. Some qualities have been gotten. And it has been proved that those results consist of theories of classical kernel estimation for continual density and further extended theories of disperse kernel estimation.

Y Dorea在2001年提出了关于上的σ-有限测度v的一般密度函数P的核估计几，其中ER，ξ是E的一个σ-域，得到了一些结果，并且验证了所得结论包含经典的连续密度核估计的结论，还进一步延伸了离散分布核估计的结论。

In this paper, the performance of SVM based on Fourier kernel is studied which aims at the regression in signal processing questions, and the influence of parameter q on performance of SVM is analyzed. A conclusion is drew that the integral of Fourier kernel in one period is a constant and the concept of equivalent kernel function width is proposed.

本文针对信号处理中的回归问题，研究了基于傅立叶核函数支持向量机的性能，并分析了参数q对其性能的影响；根据推导得出傅立叶核函数在单个周期内积分为常数的结论，并提出了等效核宽度的概念；最后的仿真结果证实了，在信号处理领域，采用傅立叶核函数的支持向量机比采用径向基核函数的有着更好的性能。

Inspired by the intuitive geometric interpretation of SVM based on convex hulls, KNNCH maps the data in the original space to the kernel space with the kernel trick and constructs a nearest neighbor classifier in the kernel space, which takes the convex hulls of training sets as the extended class sets.

该算法的设计受到支持向量机几何解释启发，利用核函数方法将数据映射到高维核空间，并在核空间构造以训练集凸包为扩展类集的最近邻分类器。

Firstly, Wavelet-Galerkin algorithm for solving the first kind of singular integral equation with the Hilbert kernel is proposed, we use the characteristic of periodic wavelet on L~2([0,1]) and Hilbert kernel to solve and make stiff matrix lower dimensions and become sparser through thresholding,thus the cost of computation is reduced. Because of the singularity of Hilbert kernel we use Tikhonov regularization method to solve the system of stiff equation. At last the convergence and numerical result of approximate solution are given. Secondly, an approach of regularization based on Fourier is presented for sideways heat equation; we give the theory proof and error estimate.

首先，提出了含Hilbert核的第一类奇异积分方程的小波伽辽金(Wavelet-Galerkin)数值算法，该算法中利用了L~2([0，1])上的周期小波和Hilbert核的特点进行处理，使得刚性矩阵维数降低并且通过阈值使得它更加稀疏，减少了计算量；由于Hilbert核的奇异性，通过Tikhonov正则化方法求解所得到的刚性方程组，给出了收敛性和数值结果；其次，对标准的一维逆热传导方程给出了一种基于Fourier正则化方法，给出了理论证明及其误差估计，解决了文献中算法与理论误差估计的不相匹配的现象，该正则化方法不仅保留了测量数据的部分高频成份，且与文献中的算法具有同样的计算量和误差估计。

Numerical results show that constant coagulation kernel has more influences on small particles than linear and quadratic coagulation kernel,whereas has less influences on big particles than linear and quadratic coagulation kernel;in the same wa...

发现常凝并核要比线性和二次方凝并核对小颗粒的影响大一些、对大颗粒的影响小一些，线性和二次方凝并核对颗粒尺度分布的时间演变影响则取决于具体情况；常冷凝核要比线性冷凝核对小颗粒的影响大一些、对大颗粒的影响小一些；连续区布朗凝并核类似于常凝并核；扩散冷凝核对颗粒尺度分布的影响界于常冷凝核和线性冷凝核之间。

Path analysis showed that N translocation rate of culm was higher for the high fresh ear yield varieties,while the N translocation rate of culm and tassel was higher for the high fresh kernel yield varieties,and the N translocation rate of leaf,bracteal leaf and ear axis was higher for the high kernel yield varieties.In addition,higher N translocation rate of leaf had a beneficial effect on N utilization efficiency as for fresh ear,fresh kernel or maturity kernel of the produce of waxy corn.

通径分析表明，鲜穗高产品种茎秆的氮素转移率较高，鲜子粒高产品种茎秆和雄穗的氮素转移率较高，成熟子粒高产品种叶片、苞叶及穗轴的氮素转移率均较高；叶片的氮素转移率高有利于品种鲜穗、鲜子粒及成熟子粒氮素利用效率的提高。

Then we introduced transition probability kernel for the hidden state process and the confederated process. In the deep research, we found that some similar parameters of state transition probability, observation symbol probability and initial state probability were involved in the transition probability kernel of the confederated process. So we can complete the training of traditional HMM parameters by training the transition probability kernel of the confederated process. To our surprised, we got the consistency of transition probability kernel of the confederated process. Meanwhile, we proved the rationality and reliability of the parameters estimation equations under the classical B-W algorithm.

然后对联合过程的转移概率核展开研究，我们根据过程的取值空间的不同，引入了隐状态空间和联合过程空间上的转移概率核，研究中发现在联合空间上的转移概率核包含了在一般的隐马氏模型的参数估计中的所有类似的三组参数(转移概率，观测概率和初始概率)，因此对传统的隐马氏模型的参数训练我们可以通过联合过程的转移概率核的训练来完成，更令我们惊奇的是联合过程的转移概率核还具有一致性；同时对于Baum提出的经典的B-W算法给出的关于模型的参数重估计公式，证明了它的合理性和可靠性，即模型经过重估计后的参数能够满足给定的单观测序列在模型下发生的概率是单调递增的。

Researches on kernel clustering algorithms. After combining K-means clustering algorithm and the theory of kernel-based learning algorithms, we propose a fast kernel K-means clustering method which is based on CPD kernel. The experiment results indicate that the clustering effect of the algorithm is better than that of K-means algorithm, the clustering speed of the algorithm is also fast than that of K-means algorithm.

核聚类算法的研究：探讨了K-均值聚类算法，通过将核学习理论与K-均值聚类算法结合，提出了一种基于CPD核函数的快速核K-均值聚类算法，并将该算法与基于Mercer核的核聚类算法进行了比较，实验结果显示，我们的方法不仅比K-均值聚类算法的聚类效果好，而且聚类速度快。

It is also known as one of the most poisonous naturally occurring substances.

它也被称为一个最自然发生的有毒物质。

The greatest stress is found at the location on the cross section where V is the largest.

最大应力出现在横截面上V为最大的地方。