pattern classification造句
例句與造句
- Study of surface emg pattern classification based on bayes decision technique
決策理論的表面肌電信號(hào)模式分類的研究 - Pattern classification of flaw was carried out with bp neural network and the feature selected
利用bp神經(jīng)網(wǎng)絡(luò)分類器及選擇的特征值對(duì)缺陷進(jìn)行模式分類。 - Pattern classification of flaw is carried out with bp neural network and the feature selected
利用bp神經(jīng)網(wǎng)絡(luò)分類器及選擇的特征值對(duì)缺陷進(jìn)行了模式分類。 - Pattern classification that is basic activity of people in living , working and studying is indispensable
模式識(shí)別是人們?nèi)粘Ｉ睢⒐ぷ?、學(xué)習(xí)中的基本活動(dòng)，須臾不可或缺。 - High - frequency information after wavelet transform is a kind of one - time feature which is not convenient for pattern classification
圖像小波變換后的高頻信息屬于小波變換的一次特征。 - It's difficult to find pattern classification in a sentence. 用pattern classification造句挺難的
- In this dissertation , the problems of pattern classification of mechanical products system is researched based on similarity measures
本課題對(duì)基于相似度量的機(jī)械產(chǎn)品系統(tǒng)模式分類的相關(guān)問(wèn)題進(jìn)行了研究。 - In this paper we look into the application of moment function and neural network in feature extraction and pattern classification of image recognition respectively
本文主要研究了矩函數(shù)和神經(jīng)網(wǎng)絡(luò)分別在圖像識(shí)別的特征提取和模式分類方面的應(yīng)用。 - Analyze the relations among pattern classification , svm and macroeconomic early warning . points out that early warning can be viewed as a process of pattern classification
分析模式分類、 svm和宏觀經(jīng)濟(jì)預(yù)警的內(nèi)在聯(lián)系，指出經(jīng)濟(jì)預(yù)警可以看作一個(gè)模式分類過(guò)程。 - Part ii describes algorithmic aspects of speech recognition systems including pattern classification , search algorithms , stochastic modelling , and language modelling techniques
第二部分講述語(yǔ)音識(shí)別系統(tǒng)中的有關(guān)算法，包括模式分類，查找算法，隨機(jī)模型，語(yǔ)言模型等技術(shù)。 - Based on the ideas of pattern classification and local decision referring whole information , a method of coupling neural network of multi - sensor information fusion is propos
從模式分類和“局部控制、全局參與”的思想出發(fā)，提出了耦合神經(jīng)網(wǎng)絡(luò)的方法來(lái)實(shí)現(xiàn)多傳感器信息融合的損傷確認(rèn)、定位及定量。 - For structural damage identification in bridge health monitoring , feature extraction of damage pattern classification was proposed and analyzed , and two feature exaction methods based on wavelet packet ( wp ) node energy were presented
摘要針對(duì)橋梁健康監(jiān)測(cè)中結(jié)構(gòu)損傷識(shí)別的特點(diǎn)，從模式識(shí)別的角度提出和分析了損傷特征提取問(wèn)題。 - Artificial neural network is a system composed of many computational elements that are connected through an appropriate set of weights for generating complex decision surface . so it can be used in pattern classification
人工神經(jīng)網(wǎng)絡(luò)是由許多以一定權(quán)值相互連接的計(jì)算單元組成的系統(tǒng)，它可以生成復(fù)雜的判決邊界，所以適用于信號(hào)分類。 - Among them kiii model is a high - dimensional chaotic neural network , which cannot only simulate the eeg waveform observed in experiments , but also the biological intelligence for pattern classification
在k系列模型中， k模型是一個(gè)高維的混沌神經(jīng)網(wǎng)絡(luò)模型， k網(wǎng)絡(luò)不僅可以模擬電生理實(shí)驗(yàn)中得到的嗅覺(jué)系統(tǒng)的eeg數(shù)據(jù)，而且也具有模式識(shí)別的能力。 - This system has important social significance and applied worthiness . in view of high dimension of ecg feature vector and complicated distribution of ecg patterns in feature space , we use fuzzy neural network to realize ecg pattern classification and recognition
本文針對(duì)ecg模式特征維數(shù)較高、樣本在特征空間的分布形態(tài)比較復(fù)雜的特點(diǎn)，采用模糊神經(jīng)網(wǎng)絡(luò)來(lái)實(shí)現(xiàn)對(duì)ecg模式的分類識(shí)別。 - Simulating living being ' s olfactory system , it improves the speed and correctness of pattern classification significantly using nonlinear dynamics method . based on freeman ' s previous work , ko ~ kiii models are analyzed in this paper
它采用非線性動(dòng)力學(xué)的方法對(duì)生物的嗅覺(jué)系統(tǒng)進(jìn)行模擬和建模，模擬嗅覺(jué)系統(tǒng)信息處理過(guò)程，為信息處理、人工智能和生物仿真提供了一套全新的思路和算法。
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