Fractional-order Riemann-Liouville Logistic mapping based pseudo-random sequence generation method
A pseudo-random sequence and generation method technology, applied in the field of pseudo-random sequence generation methods, can solve the problems of complex dynamic behavior, unguaranteed security of encryption scheme, single chaotic signal, etc.
Inactive Publication Date: 2015-12-23
NEIJIANG NORMAL UNIV
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[0003] With the improvement of computer computing power and the advancement of technology, people increasingly hope to have a pseudo-random sequence generation method with simple form but complex dynamic behavior to meet the actual needs.
Traditional chaotic models such as Logistic mapping have the defect of single chaotic signal and easy cracking
In image encryption and sound encryption, the security of the encryption scheme cannot be guaranteed
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[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0028] Please refer to the attached figure 1 , in an embodiment of the present invention, a method for generating a pseudo-random sequence based on fractional Riemann-Liouville Logistic mapping, comprising the following steps, Step 1: Fractional Riemann-Liouville Logistic mapping, Step 2: Discrimination of chaotic signals; Step Three, the output of chaotic signal; its characteristic is:
[0029] Among them in step 1: fractional order Riemann-Liouville type L...
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The invention relates to a fractional-order Riemann-Liouville Logistic mapping based pseudo-random sequence generation method, which comprises the steps of S1, fractional-order Riemann-Liouville Logistic mapping, S2, chaotic signal discrimination, and S3, chaotic signal output. In the step S1 of fractional-order Riemann-Liouville Logistic mapping, fractional-order Riemann-Liouville Logistic mapping is defined in the description, wherein n and j are non-negative integers and represent the discrete time such as 1 second, two seconds and so on, Mu(n) represents chaotic signals along with variations of n, v is the number of fractional order, and Mu is a chaotic coefficient. Particularly, the fractional-order parameter v is enabled to be 1, the fractional-order mapping (1) is simplified into classic Logistic mapping which is shown in the description. The method provided by the invention is based on fractional-order chaotic mapping. Signals relay on the fractional-order parameters, so that the provided signals have the advantages of strong randomness and high complexity degree.
Description
technical field [0001] The invention relates to a method for generating a pseudo-random sequence, in particular to a method for generating a pseudo-random sequence based on fractional Riemann-Liouville type Logistic mapping. Background technique [0002] Since the birth of chaos, due to its superior initial value sensitivity and ergodicity, chaotic signals have been widely used in secure communication, control systems, optimization theory, etc. A chaotic signal is also known as a pseudo-random sequence. Common chaotic signal generation methods include Logistic mapping, Chen system, Cai system, etc. [0003] With the improvement of computer computing power and the advancement of technology, people increasingly hope to have a pseudo-random sequence generation method with simple form but complex dynamic behavior to meet the actual needs. Traditional chaotic models such as Logistic mapping have the defects of single chaotic signal and easy to be deciphered. In image encryptio...
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IPC IPC(8): H04L9/00
Inventor 吴国成陈福来曾生达杜米特鲁·伯莱亚努
Owner NEIJIANG NORMAL UNIV