Method for identifying signal component characteristics based on predictive analysis
A technology of signal components and identification methods, applied in the field of signal processing, can solve problems such as difficult to estimate accurately, high calculation cost, difficult to ensure real-time performance, etc., and achieve the effect of accurate and efficient identification and simple calculation process
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[0052] According to figure 1 , A detailed description of the preferred embodiments of the present invention.
[0053] Such as figure 1 Shown is the flow chart of the present invention. The present invention includes the following steps:
[0054] Step 1. Input the signal to be identified x(t);
[0055] Step 2. Use the linear prediction model and the nonlinear prediction model to estimate the prediction sequence of the analyzed signal according to the increasing prediction order;
[0056] Step 2.1, use the linear prediction model to perform linear prediction analysis;
[0057] The linear predictive model (autoregressive, AR model) is suitable for the modeling of linear deterministic signals. When the signal model is selected reasonably, the data generated by the model can be used as an approximation of the real data. Therefore, prediction data can be generated by establishing a short-term linear prediction model of the observed signal.
[0058] The basic principle of linear forecasting ...
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