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Linear prediction is a mathematical operation where future values of a discrete-time signal are estimated as a linear function of previous samples. In digital signal processing, linear prediction is often called linear predictive coding (LPC) and can thus be viewed as a subset of filter theory. In system analysis (a subfield of mathematics), linear prediction can be viewed as a part of mathematical modelling or optimization. == The prediction model == The most common representation is : where is the predicted signal value, the previous observed values, and the predictor coefficients. The error generated by this estimate is : where is the true signal value. These equations are valid for all types of (one-dimensional) linear prediction. The differences are found in the way the parameters are chosen. For multi-dimensional signals the error metric is often defined as : where is a suitable chosen vector norm. Predictions such as are routinely used within Kalman filters and smoothers to estimate current and past signal values, respectively. 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「linear prediction」の詳細全文を読む スポンサード リンク
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