The larger atoms have much more complex spectra . 較重的原子具有較復(fù)雜的光譜線。
Error analysis and calibration method of complex spectrum of fourier transform infrared spectrometer 傅里葉變換紅外光譜儀復(fù)數(shù)光譜誤差分析及輻射定標方法研究
In order to overcome problems arisen from the application of x fluorescence analysis into complex spectrum produced by archaeological ceramic fragments with multi - element , low content and thick ground , we have employed the artificial neural network into the research of x fluorescence archaeology and conducted three kinds of research works . as the first one , we have applied the linear olam network ( optimal linear association memory network ) and the non - linear bp network ( back - propagation network ) respectively to analyze the complex x fluorescence spectrum of archaeological samples , and taken both results of spectrum analysis to compare with each other . the second , the method of pattern recognition of bp network was tentatively used to perform intelligent identification of production places of these archaeological samples 針對科技考古中對大量考古陶片進行產(chǎn)地研究時x熒光分析對多元素、低含量、厚基底考古陶片產(chǎn)生的復(fù)雜譜分析的問題,將人工神經(jīng)網(wǎng)絡(luò)引入x熒光考古中,進行了三方面的研究工作:一是用線性olam網(wǎng)絡(luò)(最優(yōu)線性聯(lián)想網(wǎng)絡(luò))和非線性bp網(wǎng)絡(luò)(誤差反傳導(dǎo)網(wǎng)絡(luò))分別對考古樣品的x熒光復(fù)雜譜進行解譜,并比較二者的解譜效果;二是用bp網(wǎng)絡(luò)模式識別方法對考古樣品的產(chǎn)地進行智能識別;三是為了提高網(wǎng)絡(luò)運算的可靠性和減小基體效應(yīng)及電噪聲的干擾和影響,研究并提出了三種網(wǎng)絡(luò)學(xué)習(xí)前的譜數(shù)據(jù)預(yù)處理方法。