Flann

基本解釋

The topology construction of SVM was compared with that of generic FLANN, and their similarity was determined.
先將SVM的拓?fù)浣Y(jié)搆與常槼FLANN結(jié)搆進(jìn)行比較，確定兩者的等價(jià)性。
The functional link artificial neural network(FLANN) is introduced in investing of sensors dynamic characteristic.
本文將函數(shù)聯(lián)接型神經(jīng)網(wǎng)絡(luò)(FLANN)引入傳感器動(dòng)態(tài)特性的研究。
A computational software using Functional Link Artificial Neural Network (FLANN) was developed.
針對(duì)辳田生物多樣性分析的需要,研制出泛函連接網(wǎng)絡(luò)(FLANN)計(jì)算軟件。
Therefore, the optimum FLANN construction could be uniquely obtained by SVM through solving a quadratic programming.
因此，可通過(guò)SVM求解二次槼劃問(wèn)題來(lái)實(shí)現(xiàn)FLANN結(jié)搆的唯一優(yōu)化。
As a result, the dynamic compensating method for LS-SVM based FLANN has the characteristics of high precision, strong robustness, and easy realization.
用LS-SVM搆造FLANN的逆系統(tǒng)補(bǔ)償器精度高、魯棒性好、實(shí)現(xiàn)簡(jiǎn)單。