输入向量

  • 网络Input vector
输入向量输入向量
  1. 选择一个最佳特征子集作为输入向量,对SVM分类器进行训练识别;

    An optimal subset of features is selected as input vector of SVM for training and recognition .

  2. 运用MATLAB对已训练成熟的神经网络进行仿真,便可得到输入向量的模型,完成网络识别任务。

    MATLAB was applied to simulate trained ANN , then the input vector model was gained , and network recognition was completed .

  3. 用于CMOS电路平均功耗快速模拟的输入向量对序列压缩方法:理论与实践

    Sequence Compaction for Fast Simulating Average Power Dissipation of CMOS Circuits : Theory and Practice

  4. 将经过筛选和处理过的特征作为输入向量,输入到径向基函数网络(RBF)。

    Chosen and processed features input Radial Basis Function ( RBF ) nets as input vectors .

  5. 针对非线性复杂对象,改进了基于T-S模型的模糊辨识算法:首先,提出了将输入向量的阶次辨识加入到参数辨识的方法,最终有效提高了辨识精度;

    An improved algorithm of fuzzy identification with T-S fuzzy model is proposed .

  6. SIC测试序列是指连续输入向量间只有一个位码值发生变化,可有效降低CUT内部节点翻转率。

    In SIC test sequences there is only one single bit reverse , which can reduce the toggle rate of the internal nodes in CUT .

  7. 采用PCA对输入向量进行甄别,应用粗糙集理论约简与分类无关或关系不大的向量。

    We use PCA on selecting the input vector , and use rough set on reducing the inessential factors for classification .

  8. 利用PCA算法优化网络输入向量,达到减轻网络负担的目的。

    At the same time , the PCA algorithm is used to optimize network input vector in order to reduce network burden .

  9. 以相对直径作为输入向量,以株数累积频率作为输出向量,建立直径分布的BP神经网络模型;

    Using the relative diameter as input variable and using the accumulation frequency in number of trees as output variable , the paper constructs the neural network model of tree diameter distribution .

  10. 在确定SVM的输入向量上,给出了一种P2P流特征提取运算法则,从而确定了其表达式,并进行标记以作为SVM的输入。

    A kind of algorithm is proposed for P2P flow feature extraction , at the basis of determining SVM input vector , which determines expression as input of SVM .

  11. 总体上,当作为输入向量的FTIR特征谱峰越多时,则网络的平均分类识别正确率越高;

    The LVQ neural network would show higher mean accurate rate of recognition , in general , as more FTIR characteristic frequencies were emdployed as input vectors ;

  12. 本文分别针对数据的预处理、训练数据集大小以及输入向量的大小分别进行了研究,以确定使用BP神经网络预测的一个最佳参数组合。

    Raw data preprocessing , the size of training data , as well as the size of input vectors have been studied separately , to find out the best parameter set of BP neural network prediction .

  13. 用MATLAB设计了BP神经网络和径向基神经网络,直接利用移动质量法得到的固有频率作为神经网络的输入向量。

    A BP neural network and radial basis neural network are designed by the MATLAB soft . The first natural frequencies from the moving mass method are used directly as the input vector of the neural network .

  14. 通过对车辆变速器齿轮运行状态特征信号进行时序分析和特征向量提取,并以此作为BP神经网络的输入向量进行网络训练,从而实现变速器齿轮运行状态的识别与故障诊断。

    By time series analysis and eigenvectors extraction on operation status signals of transmission gears , which are taken as inputs for neural network training , the operation status identification and fault diagnosis for transmission gears are realized .

  15. 该方法可减小自适应滤波器输入向量自相关阵的谱动态范围,提高了传统LMS算法的收敛速度和稳定性。

    This method can be used to decrease the spectrum dynamic range of auto-correlation matrix of input vector , thus improve the convergence speed and stability of traditional LMS .

  16. 运用小波变换对所选取的EEG进行多尺度小波分解,得到的不同尺度的频带分量,提取EEG在不同频段上的能量特征,作为分类器的输入向量。

    Using the method of wavelet transaction to decompose the EEG recordings into various frequency bands through multi-scale decomposition , then using wavelet coefficients to extract the energy feature that will be as the classifier input vector .

  17. 针对具有一定周期性的时间序列,本文提出的输入向量构造方法可以有效地指导LS-SVM模型进行输入向量构造,实现精确的单步和多步预测。

    Compared with other methods , for the time sequence with certain periodicity , the input vector construction method proposed in this study can achieve accurate single-step or multi-step prediction .

  18. 精确评估LDPC解码器在不同信噪比下的功耗需要在门级仿真大量的随机输入向量,以致耗费大量时间。

    To get the accurate LDPC decoder power analysis , large numbers of random input vectors should be simulated on gate-level , which consumes a lot of time .

  19. 以长江干流上游来水、洞庭湖区水位以及下游顶托等影响因子为模型输入向量,运用BP网络建立了荆江三口分流流量预报模型,该模型具有1d的预见期。

    Taking the upstream flow , water level of the Dongting lake and downstream backwater influence as input vectors , the diversion discharge prediction model is set up by BP network and the model has 1 d prediction period .

  20. 该模型可用于CMOS组合电路静态功耗估算和优化.面向基于标准单元的CMOS组合电路,利用输入向量控制技术,采用遗传算法作为求解手段,建立了CMOS组合电路静态功耗优化环境。

    A VSF-based leakage power evaluation model is then developed and used for evaluating and reducing the leakage power of CMOS combinational circuits . A leakage power reduction platform for CMOS combinational circuits by means of input vector control is presented .

  21. 通过选取G油田实际资料的22种属性作为网络的输入向量,用DPNN进行分类识别得到了含油气概率分布图,可为预测有利油气圈闭及油水分布规律提供依据。

    The 22 attributes of real data in G oilfield are selected as input vectors of network , the oilbearing probabilistic distribution map is obtained by using categorized identification , which can provide the basis of predicting prospective oil / gas traps and distributing rule of oil / water .

  22. 在此基础上,以河段水沙条件、水流主流位置及河道边界条件为输入向量,河道断面高程或冲淤变形为输出向量,建立了基于BP神经网络的河道断面变形预测模型。

    On this basis , by using flow and sediment conditions and position of main flow and river boundary as the input vectors , using cross section elevation and variation of silting as the output vectors , the model for predicting cross section deformation of river channel is established .

  23. RAED算法对误差信号和输入向量均采用分数阶操作。

    RAED algorithm uses fractional order operation for error signal and input vector .

  24. 本文通过对BP模型构建输入向量之间的非线性关系,偏差和学习步骤,提出了一个新的基于神经网络控制的变步长LMS算法。

    In order to expand the application range of the neural network by BP model building , the nonlinear relationship between the input vector , deviation and learning steps , this paper proposes a new based on neural network control variable step length LMS algorithm .

  25. 依据特征参量与接头的抗剪强度间的相关分析结果,选取了与接头抗剪切强度密切相关的特征参量作为SOM网络的归类分析的输入向量,建立了点焊接头质量分类模型。

    According to the correlation analysis between feature parameters and shear strength of joints , select these characteristic parameters which are closely related to shear strength of joints as the input vector of som network , and classify and analyze them .

  26. 利用电弧声LPC预测系数和反射系数构造输入向量,建立了支持向量机(SVM)的焊丝干伸长分类模型。

    The classifiers based on SVM ( support vector machine ) for monitoring wire extensions were established , in which the input vectors of sample sets were built with the predictor coefficients and reflection coefficients of LPC model of the arc sound signals .

  27. 通过对航天光学遥感器MTF模型和遥感图片的分析,从图像中提取出与MTF有关的特征信息,采用人工神经网络(ANN)作为工具,将这些特征信息作为ANN的输入向量。

    Through analyzing the modulation transfer function ( MTF ) of the space optical remote sensor ( SORS ) and remote images , the eigenvectors related to MTF in the image are abstracted and used as the input of artificial neural network ( ANN ) .

  28. 该文采用基于DCT变换和Gabor小波变换两种方法进行皮肤纹理的特征提取,提取的特征作为高斯混合模型(GMM)输入向量,然后通过GMM进行皮肤纹理检测。

    In this paper , two methods based on DCT and Gabor wavelet transform are respectively proposed to extract the features of skin texture . The extracted features are inputted into Gaussian mixture model ( GMM ) with which the skin texture detection is performed .

  29. 以小波能量特征向量作为概率神经网络(PNN)的输入向量集,提出了小波概率神经网络(WPNN)的损伤识别方法。

    By combining wavelet energy feature vectors with probabilistic neural network ( PNN ) in noisy conditions , a new damage identification method called wavelet probabilistic neural network ( WPNN ) was proposed .

  30. 应用输入向量控制技术降低漏电功耗的快速算法

    A Fast Algorithm for Leakage Power Reduction by Input Vector Control