數(shù)字示波器不能夠直接測(cè)量AM 調(diào)制信號(hào)，更不能測(cè)量微弱的AM 調(diào)制信號(hào)。本文運(yùn)用混沌和Elman神經(jīng)網(wǎng)絡(luò)作為檢測(cè)模型，通過(guò)混沌時(shí)間序列中重構(gòu)相空間，獲得嵌入維數(shù)，確定神經(jīng)網(wǎng)絡(luò)結(jié)構(gòu)，并采用單步預(yù)測(cè)混沌時(shí)間序列的方法，實(shí)現(xiàn)混沌背景下AM 調(diào)制信號(hào)參數(shù)檢測(cè)。實(shí)驗(yàn)說(shuō)明，該方法逼近目標(biāo)精度高，網(wǎng)絡(luò)適應(yīng)能力強(qiáng)，從混沌背景中檢測(cè)出AM 調(diào)制信號(hào)的周期和幅度，誤差小。將上述方法運(yùn)用到數(shù)字示波器設(shè)計(jì)中，可增加數(shù)字示波器測(cè)量微弱AM 信號(hào)的功能。
關(guān)鍵詞：混沌；神經(jīng)網(wǎng)絡(luò)；AM 信號(hào)；數(shù)字示波器；測(cè)量；
Abstract: Digital oscilloscope neither measures AM signal, nor weak AM signal. This paper described a method of using Elman neural network to achieve modulation signal parameters detection on chaos background. At first, reconstructed phase space on the time sequence of the chaotic background, and obtained the input dimension by lorenz equation, then confirmed network structure of the neural network, last, forecasted chaotic time series by the single-step forecasting methods. This method has properties of high approaching precision, high ability of network adaptive, high stability, not only can detect transient signal, periodic signal from the chaos background, but also can accurately detect the target signal the shape, including amplitude and period etc. These methods will be applied to the design of oscilloscopes, digital oscilloscope measurements can be realized weak signal functions.
Keywords: Chaos; Elman Networks; AM signal; Digital Oscilloscope; measure;