Segmenting detecting method for pattern domain of Duffing vibrator phase diagram

Abstract

The present invention provides an image area cutting method of the Duffing vibration generator phase map. 1. Selecting a typical Duffing vibration generator normalized equation. 2. Inserting an A / D converter in front of the typical Duffing vibration generator, inserting an area cutter in back. 3. Inputting the signals having noise to be detected into the A / D converter. 4. A quarter to a tenth of a circle of the signals to be detected is used as the converting circle of the A / D converter and is used together with a Duffing vibration generator equation to figure out the step length. 5. The result is calculated out by the Duffing vibration generator by using a fourth order Runge-Kutta algorithm and is sent to the area cutter. 6. The result is judged by the area cutter which then outputs the detected signals carrying the information of the data to be detected. In the present invention the identifying problem of two-dimensional chaos vibration generator phase map is transformed into a problem of one-dimensional detecting, and the problem that the phase map analyzing method can not be directly used for detecting the communication signals currently is solved.

Description

(1) Technical field [0001] The invention relates to the technical field of identification of phase diagrams of chaotic oscillators, in particular to a domain segmentation detection technology for separating information. (2) Background technology [0002] At present, the known methods of using chaotic oscillators to detect weak signals are all realized by analyzing the phase transition state of the chaotic oscillators, that is, by observing whether the chaotic oscillators present large-scale periodic orbital phenomena (or intermittent chaotic phenomena) or chaotic phenomena to determine the The presence or absence of a signal. [0003] So far, the main methods proposed by domestic and foreign research are: phase diagram analysis method, Lyapunov index method, Poincare section method, power spectrum method, non-integer dimensional analysis method, Melnikov function method, etc. [0004] Because there are not many chaotic systems suitable for analytical analysis, the phase dia...

AI Technical Summary

Problems solved by technology

However, because it requires a long phase trajectory data sample to ensure that the algorithm does not diverge and the solution must be started after obtaining a complete phase trajectory data sample, it has the disadvantage of not being able to provide real-time processing information

In addition, the calculation of Euler's number from the topological features of the image is still complicated, and it does not break out of the theoretical framework of two-dimensional image processing in principle.

Therefore, it does not really solve the problems faced by the phase diagram analysis method, such as the problem faced when it is used to detect communication signals in real time

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