Kernel的例句大全

First, regularize the target region with Gaussian kernel. Second, calculate its HSV color histogram which is to be used as the target model of a particle filter.

用高斯核函数正规化目标区域，进而加权计算目标的HSV颜色直方图，将该直方图作为粒子滤波器的目标模型进行跟踪。

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Infrared touch screen software system has been developed based on the embedded real-time kernel μ COS-ⅱ. The program mainly contains the task of digital data collection for the analog signal of infrared receiver, the task of coordinate information of computing and the USB data communication.

红外触摸屏的软件系统是在精简的嵌入式实时内核μC/OS-Ⅱ基础上进行开发的，主要完成了红外接收管信号的数据采集、坐标信息的计算处理、USB通信等任务。

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Association rule discovery, as a kernel task of data mining, has been studied widely.

作为数据挖掘核心任务之一的关联规则发现已经得到了广泛的研究。

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As a embedded real-time kernel based on task priority, μ C/ OS-II has been mainly used in the minitype embedded application. It has many virtues such as small size, stabile performance and free.

μC/OS-II是面向中小型应用、基于优先级的可剥夺嵌入式实时内核，其特点是小巧、性能稳定、免费公开源代码。

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In this paper, main task processing strategies of multi-tasking operating system RTX51 are discussed, with summary analysis of its internal kernel.

讨论多任务实时操作系统RTX51的主要任务处理策略，对该操作系统的内核进行了简要分析。

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Embedded systems are given computer system for special application, but common embedded system have weakness which kernel is too redundancy and task scheduling processing are too complex.

嵌入式系统是专用的计算机系统，但常用的嵌入式系统存在内核大、任务调度处理过于复杂等缺点。

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The micro-kernel of μ C/ OS-ⅱ is introduced, then the task scheduling algorithm and the priority presentation is explained.

首先，对μC/OSⅡ的内核进行了概述；其次，阐述了μC/OSⅡ的任务调度算法、优先级表示；

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Classifications of EEG during mental task based on support vector machine with optimal kernel-parameter

基于优化核参数支持向量机的意识任务分类

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The design of Embedded RTOS mainly includes the design of kernel structure, task management, time management, task synchronization and communication, the combination with TCP/ IP stack and application programming.

基于此，该RTOS的设计主要包括系统内核结构的设计、任务管理、时间管理、任务之间的通信与同步、与TCP/IP协议栈的结合以及应用程序的设计。

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Secondly it analyses the structure of kernel which is related to reservation of priority, including five functional module of μ C/ OS-ⅱ: task management module, time management module, memory management module, task synchronization and communication module, transplantation module.

其次分析了与优先级反转相关的实时内核结构，包括μC/OS-Ⅱ实时内核的五大功能模块：任务管理模块、时间管理模块、内存管理模块、任务间同步与通信模块及与移植相关的模块。

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Thirdly, with respected of the machine learning, we use least square support vector machine to train model, and lower the misclassification rate by choosing the kernel function and parameters value.

在机器学习方面：本文采用最小二乘支持向量机来训练模型，通过调整模型核函数以及选择模型参数来降低模型的错分率，提高模型的效率。

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We train the model by solving a set of independent quadratic programming problems with our derived contextual kernel.

模型的训练转化为采用我们推导出的上下文核函数求解一系列独立的二次规划问题。

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This Paper, on the basis of introducing the concept of carleson measure on unit complex super-ball of c ￣ n, discusses some relations among Bergman Kernel, Bergman space and Carleson measure on B_n.

本文在引入Cn中单位复超球Bn上的Carleson测度这一概念的基础上，研究了Bn上的Bergman核、Bergman空间以及Carleson测度三者之间的联系。

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Through learning of MLP network, Lagrange multiplier vector and threshold value b in decision function, constant in kernel function, restricted value in C-SVM and v-SVM classification can be gotten.

通过多层感知器网络的学习，获得支撑矢量机决策函数中合适的Lagrange乘子矢量及阈值b，以及非线性分类时核函数中的常系数，C-SVM分类和v-SVM分类时的约束值。

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On a Hilbert-Type Inequality with a New Kernel and Its Best Constant Factor

一个新积分核下的Hilbert型不等式及最佳常数因子

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We propose restricted locally-weighted kernel estimation for nonparametric analysis of covariance via varying coefficient models and construct related test statistic. A procedure for computing the exact p-value of the test is proposed.

对于一类协方差分析模型，本文基于变系数模型的角度，提出了约束局部加权核估计方法，并构造了相应的检验统计量，给出了计算检验p-值的精确方法。

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Third, the kernel of network test terminal and the software of application layer are developed.

接下来，对网络测试终端的内核和应用层软件进行了开发。

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CN-V model is the kernel of this dissertation, which can be divided into two phase: ( 1) Transform text from word space into concept space;

多视图概念网络模型是本文的核心内容，它的生成可以划分为两个阶段：（1）从词空间到概念空间的变换；

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Iris recognition comprises some kernel processes as iris positioning, texture feature extraction, coding and recognition.

虹膜识别通常包含虹膜定位、特征提取以及编码和识别几个关键步骤。

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Once you are in debug mode, the target machine's kernel stops.

处于调试模式之后，目标机器的内核就停止了。

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