Fuzzy Digital Signal Smoothing Method

In testing procedure, due to the existence of various interference, experimental data records collected by system test always deviate from original true data. The interference factors do not only contain measurement errors but also contain ambiguity of measuring concepts. For example, "mixed data" is the letter condition which usually exists in human science. Mixed data make contiguous sample values be mixed up and also make data curves vibrate strongly, which will produce unexpected sharp signals. We need smooth the sharp signals in order to weaken interference factors and enhance the curve's smoothness.Usually, we adopt the following signal smoothing filters: median filter, weighted mean filter, moving average filter, anti-pulse interference mean filter, amplitude limit filter and so on, these methods all have their own applicable scope. According to mixed data's character, this paper proposed a new fuzzy smoothing method, continuing to use weighted mean idea, sharing the neighboring samples' data value. But the weight factors are confirmed by building membership function of signal's sharp degree, more well and truly reflects mixed degree of signal. Besides, based on the expectation operator of fuzzy variable, we gain a new norm to estimate the signal's average angle.