多参数特征,multi-parameter feature
1)multi-parameter feature多参数特征
1.Emitter recognition based onmulti-parameter features基于多参数特征的辐射源识别技术
英文短句/例句
1.Blind recognition of joint multi-parameter OFDM signals based on high-order cumulants and trigonometric moments characteristics基于高阶累积量和三角矩的联合多参数特征OFDM信号盲识别
2.Dynamic scheduling algorithm based on multi-features in real-time operation system基于RTOS中多特征参数的动态调度算法
3.A PLANE PARAMETRIC CUBIC CURVE THAT CONTACTS THE SECOND EDGE OF THE CHARACTERISTIC POLYGON与特征多边形第二边相切的平面参数三次曲线
4.Test Analysis on Main Characteristic Parameter of Multi-aerofoil Centrifugal Fan Impeller多翼离心通风机叶轮主要特征参数的试验分析
5.The Research of Speech Features Extraction Based on Invariant Sets Multi-wavelet;基于不变集多小波的语音特征参数提取研究
6.The Identification Technique for Cashmere Based on Optimization of Multi-dimensional Characteristic Parameters基于多维特征参数优化的山羊绒鉴别技术
7.Micro-motion parameter estimation of ballistic missile target based on micro-Doppler feature基于微多普勒特征的目标微动参数估计
8.Speech Features Extraction Based on Invariant Sets Multi-wavelet基于不变集多小波的语音特征参数提取
9.Parameter Estimation of Human Upper Limbs Motion Based on Micro-Doppler Features基于微多普勒特征的人体上肢运动参数估计
10.A New Technique of Gait Feature Extraction Based on Multi-parameter Model基于多参数模型结合的步态特征提取新方法
11.About Whole Close Many Plates Wet Type Brake"s Parameter Characteristic Solide Modeling and Numerical Control Compile Programme;全封闭多盘湿式制动器的参数化特征实体造型及其数控编程
12.Supply either a job name (and job aspect), or one or more job filter parameters.请提供作业名（及作业特征），或者一个或多个作业筛选参数。
13.The Research of Mechanical Property of Contact System of Rotary Kiln with Multi-supports and Parameters Optimization;多支承回转窑接触体系的力学特征研究及参数优化
14.Study on Extracting and Application of the Multifractal Characteristic Parameters of Cement Bond Logging;声波水泥胶结测井信号多重分形特征参数提取及应用研究
15.Investigation on Fundational Features of Single Toggle Jaw Crusher with Operating Parameters;多参数可调节控制式复摆颚式破碎机基本特征研究
16.The Study of Multiwave Amplitude Equation and Inversion Method in Transverse Isotropic Medium;横向各向同性介质多波振幅特征及参数反演方法研究
17.Multi Feature Parameters Health State Evaluation of Mechanical Equipment Based on Fuzzy-AHP Methodology基于Fuzzy-AHP的机械设备多特征参数健康状态综合评价研究
18.Numerical Simulation and Analysis of SiGe HBT’s Characteristic ParametersSiGe HBT器件特征参数的数值模拟与分析
相关短句/例句
multi feature parameter多特征参数
1.This paper is aimed at the system evaluation problem of mechanical equipment caused by factors,such as the multiplicity of structure,close relevancy,and complex operating environment,from the viewpoint of functional hierarchy,a quantitative evaluation method of mechanical equipmentmulti feature parameters health state was developed on the basis of theory of fuzzy set synthesis evaluation and AHP.针对机械设备结构形式多样、关联性强、运行环境复杂等因素导致系统评价困难的问题,从机械设备功能层次结构出发,运用模糊综合评价(fuzzy set)和层次分析法(AHP),提出了一种量化评价机械设备多特征参数健康状态的新方法。
3)Multi parameter extraction多参数特征提取
4)multiparameter eigenvalue多参数特征值
5)characteristic parameters特征参数
1.Research on the range of mechanical properties andcharacteristic parameters with fabric and fusible interlinings;面料与粘合衬力学性能及特征参数配伍研究
2.Determination ofcharacteristic parameters of feature zone in elec-tron beam welding of aluminum ahoy;铝合金电子束焊接特征区域特征参数的确定
3.Experimental study ofcharacteristic parameters of severe slugging in riser-pipe systems;强烈段塞流特征参数试验研究
6)feature parameter特征参数
1.Speechfeature parameter extraction based on HHT and its application in speaker recognition基于HHT的语音特征参数提取及其在说话人识别中的应用
2.A method combining wavelet transform and watershed segmentation was put forward to obtain all thesefeature parameters.为了实现微观表面粗糙峰特征参数的获取,提出了一种结合小波分析和分水岭分割法的微观表面形貌分析方法。
3.The selecting and calculating forfeature parameters plays an important role in grinding state monitoring.在磨削状态监测中,特征参数的选择和计算起着重要的作用,频域特征参数的有效性很大程度上取决于计算频率的范围。
延伸阅读
特征提取特征提取feature extractiont6Zheng tiqu特征提取(featu了eextraction)特征选择与提取的通称。特征选择和提取是模式识别的关键环节，其任务是压缩存在于表示模式的原始测量数据中的冗余和无关的信息，提取一组对分类最有效的特征参数，以减少计算工作量，提高分类器的性能。特征参数可以从输人模式信息中选出一个子集构成，这一过程称为特征选择。新的特征参数也可以通过降维变换获得，即将输人模式从较高维数的测量空间变换到较低维数的特征空间，以一个低维特征向量表示输人模式，这一过程称为特征提取。由于特征提取的任务是求出一组对分类最有效的特征，因此首先需要一个能定量评估特征有效性的准则。分类器的误识概率可作为理想的准则，但由于估计误识概率的分布非常困难，实用时往往以其他一些准则代替。常用的准则有:基于概率距离的准则，基于类间距离的准则，基于墒函数的准则等。应用上述准则，可以通过分支定界和顺序搜索等优化算法，求得一个最优的或次优的特征集。近年来基于人工智能的启发式算法也在特征选择中得到应用。在进行降维变换以实现特征提取时，考虑到可分析性和计算可行性，一般采用线性变换方法，.最常用的是以K一L扩展为基础的线性变换。(黄泰冀)
