|
AVT Statistical filtering algorithm is an approach to improving quality of raw data collected from various sources. One way to improve signal/noise ratio is to implement filtering to separate useful signal from noise. In ideal situation the useful signal has different frequency then noise and noise is separated/filtered out by frequency discrimination using various filters. Frequency discrimination filtering is done using Low Pass, High Pass and Band Pass filtering which refers to relative frequency filtering criteria target for such configuration. Filters are created using passive and active components and sometimes are implemented using software algorithms based on FFT. Sometimes signal frequency coincides with noise frequency in real life. In this situations frequency discrimination filtering does not work since the noise and useful signal are indistinguishable. To achieve filtering in such conditions there are several algorithms available which is described below in more detail. == Averaging Algorithm == #Collect n samples of data #Calculate average value of collected data #Present/record result as actual data 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「AVT Statistical filtering algorithm」の詳細全文を読む スポンサード リンク
|