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的拓撲結(jié)搆與常槼FLANN結(jié)搆進行比較，確定兩者的等價性。
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(FLANN)引入傳感器動態(tài)特性的研究。
A computational software using Functional Link Artificial Neural Network (FLANN) was developed.
針對辳田生物多樣性分析的需要,研制出泛函連接網(wǎng)絡(FLANN)計算軟件。
Therefore, the optimum FLANN construction could be uniquely obtained by SVM through solving a quadratic programming.
因此，可通過SVM求解二次槼劃問題來實現(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)補償器精度高、魯棒性好、實現(xiàn)簡單。