输入矢量 meaning in Chinese
input with isolated common point
Examples
- Recently , art has been widely used in the field of industries , financial and market data analyses etc . in applications of art , input vector ' s coding skill is needed
如今， art已经在工业、金融与市场数据分析等领域得到应用，应用中涉及到输入矢量的编码技巧。 - Discussed are the problem of determining the number of hidden layer ' s neural units , standardizing of input vectors and choosing the initial connecting weights etc . also this paper improved and optimize the basic bp arithmetic , and designed the measurement module of dynamic liquid level and the recognition module of incipient danger & hazards based bp nn
文中讨论了网络模型中隐含层神经单元个数的选取问题，输入矢量的标准化处理问题，以及网络连接权值的初值选取问题等，同时还对基本的bp算法进行了改进、优化。设计了基于bp神经网络的动态液位测量模型和生产重大隐患和危险源的识别模型。 - Firstly , e - hmm is used to parameterize face image , the output likelihood of the e - hmm is encoded to form the input vector and is sent to the ann . by taking advantage of the discriminative training of ann , the weak discrimination of the maximum likelihood criterion can be improved , and the recognition performance can be improved by means of the learning ability of ann
该混合识别网络用e - hmm的参数来描述人脸的整体性和局部细节性特征，用e - hmm的输出似然值序列组成ann的输入矢量，利用ann的鉴别训练能力来克服e - hmm的基于最大似然准则训练算法区分力较差的弱点，同时利用ann的学习能力来提高e hmm的识别性能。 - In the process of comparison , it is found that the new vector used by this paper is suited to be taken as statistic feature of sar area objects . artificial neural network ( ann ) is always used in image classing . this thesis used bp network , rbf network and sofm network to analyze sar area objects , with gray level , average and wavelet analysis based features as the inputs
人工神经网络是模式识别的重要工具，本文分别采用bp神经网络、径向基函数( rbf )神经网络、自组织特征映射神经网络对sar图像面目标进行了分析，选用灰度值、均值、小波纹理特征等不同的特征作为输入矢量，得到了高的分类精度。 - According to the characteristic of ann itself and the complexity of factors which influence the elevation , the paper analyses the influence aspects of ann . on the promise of bridge construction precision , the paper raise determining principle and method for neural network ' s import vector in bridge construction process
根据神经网络自身的特点，以及桥梁立模标高影响因素的复杂性，对神经网络影响因素进行分析，在满足桥梁施工精度的前提下，提出了在实桥施工过程中神经网络输入矢量的确定原则和方法。