基于高階統(tǒng)計(jì)量的自適應(yīng)盲源分離算法

基于高階統(tǒng)計(jì)量的自適應(yīng)盲源分離算法:提出了一種新的自適應(yīng)盲源分離算法。在無噪音實(shí)時(shí)兩源兩傳感器的情況下, 一旦觀測信號被白化, 只需要辨識一個(gè)特定的旋轉(zhuǎn)矩陣就可以完成盲源分離, 并給出了能表征該旋轉(zhuǎn)矩陣的角的自適應(yīng)估計(jì)器。仿真結(jié)果表明, 當(dāng)滿足源峭度和不為零的條件時(shí), 這種方法是一種穩(wěn)定的和有效的分離算法。
關(guān)鍵詞: 盲源分離; 概率密度函數(shù); 高階統(tǒng)計(jì)量

Bl ind Sources Separa t ion Us ing Higher Order Sta t ist ic L IU Han, L IU D ing, L IU Xiao2yan (Xi’an U niversity of Techno logy,Xi’an 710048,Ch ina)Abstract: A new learn ing algo rithm is developed fo r b lind separat ion of independen t sou rcesignals f rom their linear m ix tu res. In the no iseless real2m ix tu re two2sou rce two2sen so r scenario, once the ob servat ion s are w h itened (deco rrelated and no rm alized) , on ly a given ro tat ion m at rix rem ain s to be iden t if ied in o rder to ach ieve the sou rce separat ion. In th is paper, an adap ter est im ato r of the angle that characterizes such a ro tat ion is derived. It show s that est im ato r converges to a stab le valid separat ion so lu t ion w ith the on ly condit ion that the sum of sou rce ku rto sis be dist inct f rom zero. Sim u lat ion demon st rate the validity of the algo rithm.
Key words: b lind sou rce separat ion; p robab ility den sity funct ion; h igher o rder stat ist ic