The detection algorithm based on chaotic prediction error is used to detect objects under a chaotic background.

Because there is a dynamic tuning to the prediction error in the controller design, and the proportional integration type cost function is used, so the controller has strong robustness to unmodelled dynamic.

It uses different embedding dimensions and delay time to reconstruct phase space,and compares the prediction errors,then the embedding dimension and delay time that make the smallest error are the best one.

Furthermore, the difference is studied in more details in terms of the de-trending effect, stabilization method, convergence speed variance of estimate s limit distribution, forecasting errors, dynamic features and so on.

The forecasting error that the model may produce is estimated.

This paper studies the relation between the structure of the forecasting error information matrix and the nature of the combination forecasting method of non negative weights.

This paper seeks to describe the investment recommendations,earning forecast error and the source of the error.

In order to avoid double-talk detection, an AEC algorithm based on Filter-LMS algorithm is proposed, which applies the sum of far-end signal and output error instead of the far-end signal to activiate the forecast error filter, and thus to contributes to reducing the influence of near-end signal.

Firstly, the present machining error prediction technologies and their disadvantages were analyzed and compared.

It can do pixel prediction and error prediction by function evolutional mode during lossless image compressing to improve the performance of lossless image compress.