vector algorithms造句
例句與造句
- New multi - class support vector algorithm and its application in fault diagnosis
一種新型多分類支持向量算法及其在故障診斷中的應(yīng)用 - The mathematical model of attitude solving algorithm on high dynamic aircraft was established , and the method which used rotation vector algorithm to solve attitude angle was discussed , and the method was compared with quaternion
摘要建立了高動(dòng)態(tài)飛行器姿態(tài)解算的數(shù)學(xué)模型，探討了利用等效旋轉(zhuǎn)矢量法解算姿態(tài)角的方法，并與四元數(shù)法進(jìn)行了比較。 - Then as to the disadvantage of the tss native algorithms we bring for word a new algorithms which is bit vector algorithms base on rule length and the result of program show the performance of new algorithms is better than the native one
然后本文針對(duì)tss原始算法設(shè)計(jì)的缺陷，提出了基于規(guī)則長度的比特向量算法，仿真結(jié)果顯示該算法的性能優(yōu)于tss的原始算法。 - Introduce the traditional two samples rotation vector algorithm and three samples rotation vector algorithm , which fit the incremental angular condition . but , the output of fiber optic gyro is angular rate of the vehicle , the error would increase serious if use traditional algorithm
由于光纖陀螺儀輸出為角速率信號(hào),而傳統(tǒng)的旋轉(zhuǎn)矢量算法輸出為角增量信號(hào),采用角增量提取算法,旋轉(zhuǎn)矢量精度會(huì)大幅大降。 - Reference to mpeg - 7 standards , mainly researches feature extracting schemes of video visual information . it includes histogram refinement in rgb color space , histogram in hsv color space , color coherence vectors algorithm and homogeneous texture descriptor extraction algorithm
論文中主要研究的視覺特征提取方法有： rgb顏色空間的改進(jìn)直方圖法、 hsv顏色空間的直方圖統(tǒng)計(jì)、顏色相關(guān)向量法和提取同類紋理描述符算法。 - It's difficult to find vector algorithms in a sentence. 用vector algorithms造句挺難的
- 3 . to meet the real - time demand in the robot soccer competition , this thesis proposed a color image segmentation method using improved threshold vector algorithm in yuv color space . the new algorithm can classify 8 colors in one time , so the speed of the algorithm is improved a lot
針對(duì)足球機(jī)器人系統(tǒng)中對(duì)視覺系統(tǒng)實(shí)時(shí)性方面的具體要求，提出了一種改進(jìn)了閾值向量彩色圖像分割方法，對(duì)于一個(gè)未知顏色的像素點(diǎn)，一次計(jì)算就能夠判斷其顏色，并將其進(jìn)行分類。 - This dissertation develops research work for some fields in which ground clutter suppression algorithm may be used for airborne phased - array radar , software design of 3dt - - stap algorithm with adaptive space - frequence steer vector algorithm is completed for clutter suppression realtime processing system based on tigersharc ts101 chip
本論文圍繞機(jī)載相控陣?yán)走_(dá)的空時(shí)二維處理技術(shù)展開研究工作,主要任務(wù)是為系統(tǒng)選擇地雜波抑制的算法,并完成以浮點(diǎn)dsp芯片( ts101 )為核心的基于3dt - Secondly , the improved rotation vector algorithms in the pure coning motion are discussed and the computing burden is compared with each other . lastly , computer simulations are executed to test the algorithms " performance . the results show that the rotation vector algorithms can improve the precision of the attitude calculation effectively
分析了高動(dòng)態(tài)環(huán)境下捷聯(lián)慣導(dǎo)圓錐誤差的產(chǎn)生機(jī)理，研究了純錐運(yùn)動(dòng)條件下姿態(tài)更新的旋轉(zhuǎn)矢量?jī)?yōu)化算法，對(duì)各算法的計(jì)算量和精度進(jìn)行了對(duì)比，最后對(duì)各算法進(jìn)行了計(jì)算機(jī)仿真，仿真結(jié)果表明：旋轉(zhuǎn)矢量算法能有效提高姿態(tài)算法的精度； 2 - ( 2 ) the influence to classification result is highly effected by using different classifier , for example , the center - vector algorithm obtains better classification results than other two algorithms . with the character feature , the average recall is 80 . 73 % , and the average precision is 82 . 94 % , and with the chinese - word feature , the average recall is 83 . 6 % , and the average precision is 85 . 97 % . different corpuses influence the classification result . for example , the average recall is 89 . 31 % and the average precision is 88 . 33 % , by using the news web pages as corpus from the web site " www . sina . com . cn " , which adopt the center - vector algorithm to structure classifier and select chinese - word as feature
對(duì)三種分類器分別以字、詞為特征進(jìn)行分類測(cè)試、分析發(fā)現(xiàn)：使用相同的分類算法，用詞作為特征項(xiàng)，比以字作為特征的分類效果好；用不同的算法構(gòu)造分類器對(duì)分類效果的影響很大，如中心向量算法在字、詞特征下的分類效果優(yōu)于其他兩算法；在以字為特征的情況下，該算法的平均查全率80 . 73 ，平均查準(zhǔn)率82 . 94 ；在以詞為特征的情況下，該算法的平均查全率83 . 6 ，平均查準(zhǔn)率85 . 97 ；選用語料不同對(duì)分類效果也有影響，如用新浪網(wǎng)( www . sina . com . cn )網(wǎng)頁語料進(jìn)行測(cè)試，使用中心向量法分類器和詞作為特征的情況下，平均準(zhǔn)確率為89 . 31 ，平均查全率為88 . 33 。 - Based on these descriptions , a nd model called support vector data description ( svdd ) is founded . ( 2 ) a qualitative guide for setting those parameters in oc - svms is investigated . a multi - layer high - speed training strategy was proposed to enable support vector algorithm to handle large training data
( 2 )通過分析支持向量機(jī)中模型參數(shù)對(duì)檢測(cè)結(jié)果的影響,給出了確定這些參數(shù)的一般方法;提出了一種分層式的快速訓(xùn)練方法,克服了樣本個(gè)數(shù)和維數(shù)對(duì)支持向量算法應(yīng)用的制約,提高了訓(xùn)練效率。 - First , the theories of the music algorithm and the esprit are presented here . conventional algorithms are limited by the array configuration , and a constructing vectors algorithm , which uses the correlative function of array data , is proposed in this paper . this algorithm is n ' t restricted within the special array configuration , and it is also very steady
在介紹了多重信號(hào)分類( music )算法和旋轉(zhuǎn)不變技術(shù)( esprit )的基本原理后,考慮到常規(guī)的算法都受到陣列形式的限制,本文在esprit算法的基礎(chǔ)上,提出了一種利用陣元數(shù)據(jù)的相關(guān)函數(shù)構(gòu)造向量的算法,該算法不要求特定陣列結(jié)構(gòu),且有一定的穩(wěn)健性。 - In this paper , we begin with the analysis of wavelet transform . after the analysis of image wavelet coefficients and methods of image compression , a method of vector - constitution among different subbands , making verctor book using pcc + lbg , and fast vq is presented . at the same time a better compression performance is improved by using multistage vector algorithm , the design of this algorithm based on dsps is given at the end of this paper
該算法充分利用了小波分解后各子帶間的相關(guān)性，跨子帶構(gòu)造高維數(shù)矢量，利用改進(jìn)的漸進(jìn)構(gòu)造聚類( pcc )結(jié)合lbg的算法生成了具有代表性的最優(yōu)碼書，并提取特征矢量快速實(shí)現(xiàn)矢量量化，最后通過二級(jí)量化進(jìn)一步降低矢量量化的復(fù)雜度。 - Statistical learning theory derives necessary and sufficient conditions for consistency and fast rate of convergence of the empirical risk minimization principle , which is the basis of most traditional learning algorithms . it also theoretically underpins the support vector algorithms . support vector learning algorithm is based on structural risk minimization principle
傳統(tǒng)的學(xué)習(xí)算法大多是基于經(jīng)驗(yàn)風(fēng)險(xiǎn)最小化原則的，統(tǒng)計(jì)學(xué)習(xí)理論給出了經(jīng)驗(yàn)風(fēng)險(xiǎn)最小化原則一致和快速收斂的充分和必要條件，并且為支持向量算法做了理論支持。