Digital circuit pseudo-random data generation device and method based on hyper-chaos theory

Abstract

The invention relates to the technical field of statistics and experimental design, and discloses a hyper-chaos theory-based digital circuit pseudo-random data generation device and method, and the device comprises a hyper-chaos circuit operation module which is used for carrying out the operation according to a preset hyper-chaos system mathematical expression, and generating a hyper-chaos state variable; and the improved Euler algorithm solving module is used for receiving the state variable output by the hyper-chaotic circuit operation part, and carrying out iterative calculation by using an improved Euler algorithm to generate random data. According to the digital circuit pseudo-random data generation device and method based on the hyper-chaos theory, the hyper-chaos circuit operation module and the improved Euler algorithm solving module are designed, so that low-power-consumption and high-precision simulation of complex dynamic behaviors of a hyper-chaos system in a digital circuit is effectively realized; the problems of high power consumption and complicated implementation in the traditional chaotic system digital circuit design are solved, and a scheme is provided for the practical application of the chaos theory in the fields of encryption, communication and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of statistics and experimental design, and in particular to a digital circuit pseudo-random data generating device and method based on hyperchaos theory. Background Art

[0002] The application of chaotic systems, especially hyperchaotic systems, in digital circuit design has attracted much attention due to their unique nonlinear dynamic characteristics. However, the design of digital circuits for chaotic systems is relatively complex, which is mainly reflected in the implementation of the system mathematical expression and the selection and layout of circuit elements. Chaotic systems usually contain multiple interdependent variables and complex nonlinear relationships. The implementation of these characteristics in digital circuits requires precise operation units and complex control logic.

[0003] Compared with ordinary chaotic systems, hyperchaotic systems have more complex dynamic behaviors and higher nonlinearity, which makes the design of digital circuits for hyperchaotic systems more complicated. In the process of circuit implementation, in order to maintain the hyperchaotic state, high-precision computing units and stable control logic are required, which often leads to an increase in circuit power consumption. Therefore, the high power consumption of digital circuits for hyperchaotic systems has become a major obstacle to their widespread application. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention proposes a digital circuit pseudo-random data generation device and method based on hyperchaos theory to solve the above technical problems.

[0005] In a first aspect, a digital circuit pseudo-random data generating device based on hyperchaos theory is provided, comprising:

[0006] A hyperchaotic circuit operation module is used to perform operations according to a preset hyperchaotic system mathematical expression to generate hyperchaotic state variables;

[0007] The improved Euler algorithm solving module is used to receive the state variables output by the operation part of the hyperchaotic circuit, and use the improved Euler algorithm to perform iterative calculations to generate random data.

[0008] Furthermore, the hyperchaotic circuit operation module includes:

[0009] The four operation units correspond to the four sub-expressions of the mathematical expression of the hyperchaotic system, and are used to calculate different characteristics, dissipation rate, nonlinear behavior, external forcing or driving terms of the system.

[0010] Furthermore, the mathematical expression of the hyperchaotic system is:

[0011] {X=a(yx)+w

[0012] {y=cx-y-xz

[0013] |z=xy-bz

[0014] | w =-yz+rw

[0015] Among them, a, b, c, r are system parameters, and x, y, z, w are system state variables.

[0016] Furthermore, the improved Euler algorithm solving module includes a state machine, and the state machine is configured as follows:

[0017] Receiving state variables from a hyperchaotic circuit operation module;

[0018] Applying the modified Euler algorithm to iteratively process the received state variables to generate random data;

[0019] The state machine has at least three operating states for controlling the iterative process of the improved Euler algorithm.

[0020] Furthermore, the state machine performs truncation processing on data in the S1, S2 and S3 states.

[0021] Furthermore, the improved Euler algorithm solution module uses a preset initial value as a starting condition during each iterative calculation.

[0022] Furthermore, the initial values ​​include initial values ​​of system parameters and state variables.

[0023] In a second aspect, a method for generating pseudo-random data in a digital circuit based on hyperchaos theory is provided. The device for generating pseudo-random data in a digital circuit based on hyperchaos theory according to any one of the above-mentioned items comprises the following steps:

[0024] Through the hyperchaotic circuit operation module, operations are performed according to the preset hyperchaotic system mathematical expressions to generate hyperchaotic state variables;

[0025] The state variables output by the hyperchaotic circuit operation module are received, and the improved Euler algorithm is used for iterative calculation to generate random data.

[0026] Furthermore, the iterative calculation of the modified Euler algorithm includes at least three steps:

[0027] The first step is to calculate and store the initial iteration results;

[0028] The second step is to add the initial iteration result to the result of the current hyperchaotic circuit operation module, perform a new iteration calculation and store the result;

[0029] The third step is to calculate the average of the current result and the results of two iterations, and add them together to obtain the final random data output result.

[0030] The invention adopting the above technical solution has the following advantages:

[0031] The present invention effectively realizes the low-power and high-precision simulation of the complex dynamic behavior of the hyperchaotic system in the digital circuit by designing the hyperchaotic circuit operation module and the improved Euler algorithm solution module, which is beneficial to solving the problems of high power consumption and complex implementation in the digital circuit design of the traditional chaotic system, and provides a solution for the practical application of chaos theory in the fields of encryption and communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the specific implementation of the present invention, the following will briefly introduce the drawings required for use in the specific implementation. In all the drawings, each element or part is not necessarily drawn according to the actual scale.

[0033] Figure 1 This is a circuit structure diagram of a digital circuit pseudo-random data generation device and method based on hyperchaos theory of the present invention;

[0034] Figure 2 It is a schematic diagram of a state machine in a digital circuit pseudo-random data generation device and method based on hyperchaos theory of the present invention;

[0035] Figure 3 It is the x, y, z, w result diagram of the simulation output in the digital circuit pseudo-random data generation device and method based on hyperchaos theory of the present invention;

[0036] Figure 4 This is a diagram of Shapiro-Wilk analysis results in the digital circuit pseudo-random data generation device and method based on hyperchaos theory of the present invention;

[0037] Figure 5 It is a result diagram of comparing entropy value and standard entropy value in the digital circuit pseudo-random data generation device and method based on hyperchaos theory of the present invention;

[0038] Figure 6 The present invention is a MATLAB drawing display of a digital circuit pseudo-random data generation device and method based on hyperchaos theory;

[0039] Figure 7 The second MATLAB drawing is shown in the digital circuit pseudo-random data generation device and method based on hyper-chaos theory of the present invention;

[0040] Figure 8 This is a diagram showing the results of circuit power consumption analysis in the digital circuit pseudo-random data generation device and method based on hyperchaos theory of the present invention. DETAILED DESCRIPTION

[0041] The following embodiments of the technical solution of the present invention are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and are therefore only used as examples, and cannot be used to limit the protection scope of the present invention.

[0042] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should be the common meanings understood by technicians in the field to which the present invention belongs. The terms "first", "second", etc. in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so as to implement the embodiments of the present disclosure described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. Unless otherwise specified, the term "multiple" means two or more. In the embodiments of the present disclosure, the character " / " indicates that the objects before and after are in an "or" relationship. For example, A / B means: A or B. The term "and / or" is a description of the association relationship of objects, indicating that there can be three relationships. For example, A and / or B means: A or B, or, A and B. The term "corresponding" can refer to an association relationship or a binding relationship, and A and B correspondingly refer to an association relationship or a binding relationship between A and B.

[0043] like Figures 1 to 8 As shown, the digital circuit pseudo-random data generating device based on hyperchaos theory of the present invention comprises:

[0044] A hyperchaotic circuit operation module is used to perform operations according to a preset hyperchaotic system mathematical expression to generate hyperchaotic state variables;

[0045] The improved Euler algorithm solving module is used to receive the state variables output by the operation part of the hyperchaotic circuit, and use the improved Euler algorithm to perform iterative calculations to generate random data.

[0046] Specifically, based on the hyperchaotic system theory, the modified Euler algorithm is selected to design the corresponding digital circuit, and the high bits of the data are truncated to retain the low bits, so that the data changes are irregular. Due to the uncertainty of the chaotic system, the results produced by the circuit each time become more complex and difficult to predict, making the calculation results even more random.

[0047] The present invention effectively realizes the low-power and high-precision simulation of the complex dynamic behavior of the hyperchaotic system in the digital circuit by designing the hyperchaotic circuit operation module and the improved Euler algorithm solution module, which is beneficial to solving the problems of high power consumption and complex implementation in the digital circuit design of the traditional chaotic system, and provides a solution for the practical application of chaos theory in the fields of encryption and communication.

[0048] In some embodiments, the hyperchaotic circuit operation module includes:

[0049] The four operation units correspond to the four sub-expressions of the mathematical expression of the hyperchaotic system, and are used to calculate different characteristics, dissipation rate, nonlinear behavior, external forcing or driving terms of the system.

[0050] In some embodiments, the hyperchaotic system mathematical expression is:

[0051] {X=a(yx)+w

[0052] {y=cx-y-xz

[0053] |z=xy-bz

[0054] | w =-yz+rw

[0055] Among them, a, b, c, r are system parameters, and x, y, z, w are system state variables.

[0056] Specifically, the hyperchaotic circuit operation part:

[0057] The design is based on the Lorenz system, which is divided into four parts: A controls the different characteristics of the system, B controls the dissipation rate of the system, C affects the nonlinear behavior of the system, and D represents the external force or driving term. These correspond to the four expressions of the hyperchaotic system theory: A: X = a(yx) + w, B: y = cx-y-xz, C: z = xy-bz, and D: w = -yz + rw.

[0058] In some embodiments, the modified Euler algorithm solving module includes a state machine, and the state machine is configured to:

[0059] Receiving state variables from a hyperchaotic circuit operation module;

[0060] Applying the modified Euler algorithm to iteratively process the received state variables to generate random data;

[0061] The state machine has at least three operating states for controlling the iterative process of the improved Euler algorithm.

[0062] In some embodiments, the state machine performs truncation processing on data in the S1, S2, and S3 states.

[0063] In some embodiments, the improved Euler algorithm solving module uses a preset initial value as a starting condition during each iterative calculation.

[0064] In some embodiments, the initial values ​​include initial values ​​of system parameters and state variables.

[0065] In some other embodiments, a method for generating pseudo-random data in a digital circuit based on hyperchaos theory is provided. A device for generating pseudo-random data in a digital circuit based on hyperchaos theory according to any one of the above items comprises the following steps:

[0066] Step S01, performing calculations according to a preset hyperchaotic system mathematical expression through a hyperchaotic circuit calculation module to generate hyperchaotic state variables;

[0067] Step S02, receiving the state variables output by the hyperchaotic circuit operation module, and using the improved Euler algorithm to perform iterative calculations to generate random data.

[0068] In some embodiments, the modified Euler algorithm iterative calculation includes at least three steps:

[0069] The first step is to calculate and store the initial iteration results;

[0070] The second step is to add the initial iteration result to the result of the current hyperchaotic circuit operation module, perform a new iteration calculation and store the result;

[0071] The third step is to calculate the average of the current result and the results of two iterations, and add them together to obtain the final random data output result.

[0072] Specifically, in the state machine:

[0073] S1: The first step of the improved Euler algorithm is based on the set initialization, where a=8, b=2, c=25, r=1, x=1048576, y=z=w=524288. The data is in decimal system. Based on the counting of the hyperchaotic circuit operation part, the corresponding X_k1, Y_k1, Z_k1, W_k1 are obtained and stored.

[0074] Subsequently, the counting results of the operation part of the hyperchaotic circuit are stored in the variables X_k1, Y_k1, Z_k1, and W_k1.

[0075] S2: Perform the second step of the improved Euler algorithm, add X_k1, Y_k1, Z_k1, W_k1 to the count result of the current hyperchaotic circuit operation part as the input value of the new hyperchaotic circuit operation part, and then send the result calculated by the hyperchaotic circuit operation part to the result X_k1, Y_k1, Z_k1, W_k1 obtained by running S1, and perform addition operations on them to obtain X_k2, Y_k2, Z_k2, W_k2.

[0076] S3: Perform the third step of the improved Euler algorithm, add the result of the current hyperchaotic circuit operation part counting and the result of averaging X_k1, Y_k1, Z_k1, W_k1 and X_k2, Y_k2, Z_k2, W_k2 respectively, and then add them to obtain the final random data output result.

[0077] It is worth noting that except for the hyperchaotic circuit operation part, data truncation is required at other times. The purpose is to reduce the use of registers, reduce the overall power consumption of the circuit, and enhance the randomness of the output data.

[0078] Run the simulation to output x, y, z, w. The results are as follows Figure 3 shown.

[0079] First, use Shapiro-Wilk to perform a simple analysis, and the results are as follows Figure 4 shown.

[0080] Then use the entropy method to measure the degree of chaos:

[0081] Entropy is an important concept in information theory, which is used to measure the randomness and uncertainty of data. If the entropy value of the data is high, it indicates that it is more random; conversely, if the entropy value is low, it may indicate that there is a certain regularity in the data.

[0082] The analysis was performed using a Python design program and compared with the random numbers generated by random in Python. The entropy value of the random numbers generated by random in Python is considered to be the "standard entropy value", and the entropy value of the data generated by the simulation of the present invention is considered to be the "comparative entropy value".

[0083] like Figure 5 As shown, it can be seen that the data generated by the circuit of the present invention has good randomness.

[0084] The data results generated by the simulation are plotted using Matlab. Figure 6-7 As shown, it has good randomness.

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A digital circuit pseudo-random data generation device based on hyperchaos theory, characterized in that: include: A hyperchaotic circuit operation module is used to perform operations according to a preset hyperchaotic system mathematical expression to generate hyperchaotic state variables; The improved Euler algorithm solving module is used to receive the state variables output by the operation part of the hyperchaotic circuit, and use the improved Euler algorithm to perform iterative calculations to generate random data.

2. The device according to claim 1, characterized in that The hyperchaotic circuit operation module comprises: The four operation units correspond to the four sub-expressions of the mathematical expression of the hyperchaotic system, and are used to calculate different characteristics, dissipation rate, nonlinear behavior, external forcing or driving terms of the system.

3. The device according to claim 2, characterized in that The mathematical expression of the hyperchaotic system is: {X=a(yx)+w {y=cx-y-xz |z=xy-bz | w =-yz+rw Among them, a, b, c, r are system parameters, and x, y, z, w are system state variables.

4. The device according to claim 1, characterized in that The improved Euler algorithm solving module includes a state machine, and the state machine is configured as follows: Receiving state variables from a hyperchaotic circuit operation module; Applying the modified Euler algorithm to iteratively process the received state variables to generate random data; The state machine has at least three operating states for controlling the iterative process of the improved Euler algorithm.

5. The device according to claim 4, characterized in that The state machine performs truncation processing on data in the S1, S2 and S3 states.

6. The device according to claim 5, characterized in that The improved Euler algorithm solution module uses a preset initial value as a starting condition during each iterative calculation.

7. The device according to claim 6, characterized in that The initial values ​​include initial values ​​of system parameters and state variables.

8. A method for generating pseudo-random data in a digital circuit based on hyperchaos theory, characterized in that: The digital circuit pseudo-random data generation device based on hyperchaos theory according to any one of claims 1 to 7 comprises the following steps: Through the hyperchaotic circuit operation module, operations are performed according to the preset hyperchaotic system mathematical expressions to generate hyperchaotic state variables; The state variables output by the hyperchaotic circuit operation module are received, and the improved Euler algorithm is used for iterative calculation to generate random data.

9. The method according to claim 8, characterized in that The modified Euler algorithm iterative calculation includes at least three steps: The first step is to calculate and store the initial iteration results; The second step is to add the initial iteration result to the result of the current hyperchaotic circuit operation module, perform a new iteration calculation and store the result; The third step is to calculate the average of the current result and the results of two iterations, and add them together to obtain the final random data output result.

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