Based On Chaos Theory, Nonlinear Signal Prediction And Testing

The development of modern electrical technology causes phenomenal progress to be made in the improvement of the signal processing methods. The problems in signal processing are becoming more and more complex, many linear signal processing methods can't meet the request, so, nonlinear signal processing methods become more and more widely used. The appearance of chaotic theory brings nonlinear signal processing more convenience, and promotes the development of nonlinear signal processing. In the text, direct sequence spread spectrum signal (DSSS signal) is the main object, and some nonlinear methods based on chaotic theory, used in the prediction of signal and detection of signal is studied. The main contents in this text are:1. Several nonlinear predicting methods are analyzed and studied, and computer emulations show the feasibility and efficiency of these methods. The advantages and disadvantages of each predicting method, when it is used to predict different kinds of signals, are analyzed.2. The chaotic character of DSSS signal is studied. DSSS signal is a widely used signal in the communication. It is easily produced, has good privacy protection and interference immunity. Theoretical analysis and computer simulation proves that DSSS signal has chaotic character, and the cognition of DSSS signal in chaotic theory makes this kind of signal be better used of in more areas.3. The detection of delicate signals in chaotic noise is studied. The principle of the error-based detecting method used in the detection of periodical signals is theoretically analyzed, and simulations are carried out to show its feasibility and efficiency. The efficiency of the error-based detecting method when it is used to detect DSSS signal in chaotic noise is analyzed theoretically, and simulations are carried out to show its feasibility and efficiency.4. This error-based detecting method is improved, that is, predicting the chaotic noise is changed to estimating the chaotic noise. A predicting method is improved to an estimating method to estimate the chaotic noise. Then the time used to train the parameters is saved, and no invalid detection will be gotten even if signals come into...