A classification method based on Support Vector Machine (SVM) is given in the digital modulation signal classification.
给出了一种基于支持向量机的数字调制信号分类器设计方法。
A new thought of combining frequency estimate method based on FFT with that based on multiple signal classification (MUSIC) is presented.
提出了将基于FFT的频率估计法和基于多重信号分类(MUSIC)的频率估计法相结合的新思路。
Information on the steering vector is not exploited when estimating signal or noise subspaces in the standard multiple signal classification (MUSIC) method.
常规多信号分类(MUSIC)在估计信号或噪声子空间时未利用阵列的方向矢量信息。
Simulation results show that the communication signal classification method based on BAM/NBAM is effective, its performance is better than the traditional linear classification method.
结果表明，基于BAM/NBAM的通信信号分类方法是有效的，其性能优于传统的线性分类方法。
The emphasis and difficulty lie in how to extract characteristic of signal efficiently, that is, the problem of seeking classification criteria.
其重点与难点在于如何有效的提取信号中的特征量，即分类标准的找寻问题。
The extracting process is to throw off the useless information and look for the most efficient signal feature to form a pattern feature vectors for classification with mathematics tools.
特征提取的依据是利用有关数学工具，去掉对分类无用的信息，寻找最有效的信号特征来构成用于分类识别的模式特征向量。
The classification and identification of communication signal is a typical statistical pattern identification.
通信信号的分类识别是一种典型的统计模式识别问题。
The result is accord with geological sample and sediment chart, so this method can be applied on sediment classification of narrow-band pulse echo sound signal.
分析结果与地质采样结果及海图均吻合，说明本文提出的方法应用于窄带脉冲信号的海底底质分类是适用的。
But it needs prior knowledge of speech signal and its classification and decision making capability is weak.
但它存在需要语音信号的先验知识，分类决策能力弱等缺点。
A simulation on computer showed that using the structure, the precision and sensitivity of signal recognition and classification were improved.
计算机模拟表明，该结构提高了信号分类识别的精度和灵敏度。
Classification is to classify signal into its category according to the observed value of feature extracted.
分类识别是依据信号特征的观测值将其分到不同类别中去。
To solve the classification of dynamic signal, this paper proposed a feedback process neural networks model and classification methods based on this model.
针对动态信号模式分类问题，提出了一种反馈过程神经元网络模型和基于该模型的分类方法。
Following discussions on the principle of Doppler, the classification of the deformation, and analysis of signal spectrum, a continuous and rapid method for the measurement is presented.
通过对超声多普勒原理、路面变形的分类研究及测试信号谱分析的详细讨论和研究，给出了一种连续、快速检测沥青路面变形情况的方法。
Most pattern classification algorithms rely heavily on the shape of the signal, which can vary considerably with frequency.
因为大多数模式分类算法与信号的形状密切相关，而信号的形状很大程度上随检测频率的变化而变化。
The method with different order amplitude moments makes use of the product moment of signal magnitude for classification of MPSK/MQAM signals.
不同阶幅度矩进行调制分类的方法利用MPSK/MQAM信号每符号段波形起始点与其它点幅度的乘积统计矩特征进行调制分类。
Spectrum analysis is the most important branch in radar signal processing and significant of radar target classification and feature detection.
谱分析是雷达信号处理的重要组成部分，对目标分类、特征检测均有重要意义。
Based on the classification of signal characteristic, a model of quantitative recognition for oil well tubing defects was built.
建立了基于特征分类的油管缺陷量化识别模型。
Based on fuzzy classification the features of AE signal were optimized, and on this basis a general conclusion of optimizing AE characteristics was reached.
利用模糊聚类特征优选方法对声发射传感器特征信息进行优选，并在此基础上给出了模糊聚类优选声发射特征的一般结论。
Using this model, together with some necessary post-process work, it can synthesize smooth, realistic face speech animation independent of classification of language only with speech signal.
使用该模型，加上一些必要的后期处理工作，就可以通过输入的语音信号合成语种无关的、平滑的、并富有真实感的人脸语音动画。
The classification technique uses various features of the signal amplitude, frequency, and power spectrum applied to the fuzzy classifier.
本文研究了一种基于模糊分类的调制信号识别方法，即提取信号时域、频域、功率谱等统计特性，利用模糊分类器进行分类识别。
The work of this paper can be divided into five parts: signal collecting, signal detection, classification recognition, terminal display and experimental analysis.
可以将本文的工作大致分为五个部分：数据采集、信号探测、分类识别、终端显示、实验分析。
A typical BCI system consists of several parts, such as signal acquisition, feature extraction, classification algorithm, command output and so on.
一个BCI系统是由信号采集、特征提取、分类算法、命令输出等单元组成。
In this paper, defects for NDT are classified with neural network which USES features extracted from signal processing. Then classification results from networks are fused with fuzzy integral.
在无损检测信号处理和特征构造的基础上，用神经网络对缺陷进行识别，然后运用模糊积分对多个神经网络的分类结果进行融合。
The time - varying properties can be extracted better when signal being transformed on 2d coordinate plane for the purpose of signal recognition and classification.
将一维信号变换到二维坐标平面往往更有利于描述信号的时变特征，从而实现信号的分类识别。
YANG Jie. ECG signal detection and pattern classification methods of research [d]. Hangzhou: Hangzhou Normal University, 2014.
[5]杨杰。心电信号的检测与模式分类方法的研究[D]。杭州：杭州师范大学，2014。
Here the focus is the front, designing a high classification BCI only using simple sensibilities mental task EEG signal and indication a method using this BCI to sort many kinds of tasks.
本文的工作重点在前端，设计了一种进行意识思维任务时脑电信号(EEG)的高辨识率二分类bci，并提出了一种应用此二分类bci进行多种工作任务识别的方法。
The analysis thus produces a signal based on twenty five different sound qualities and variables, which can then be fed into a computer-based classification system.
通过分析产生一个由25个不同音质和变量的信号，然后将信号输入计算机分类系统。
The analysis thus produces a signal based on twenty five different sound qualities and variables, which can then be fed into a computer-based classification system.
通过分析产生一个由25个不同音质和变量的信号，然后将信号输入计算机分类系统。
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