Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A Tristable Logic Stochastic Resonance Method

A stochastic resonance and stochastic resonance model technology, applied in the field of logic implementation, can solve problems such as insufficient smoothness of the output waveform, large output noise of stochastic resonance of bistable logic, and influence on logic output signal detection and processing, etc., to achieve easy adjustment and low noise , Wave smooth effect

Active Publication Date: 2021-09-17
ANHUI UNIVERSITY
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the output noise of bistable logic stochastic resonance is relatively large, and the output waveform is not smooth enough, which further affects the detection and processing of subsequent logic output signals.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Tristable Logic Stochastic Resonance Method
  • A Tristable Logic Stochastic Resonance Method
  • A Tristable Logic Stochastic Resonance Method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0038] According to the step S1 of the method of the present invention, the tri-stable logical stochastic resonance model is built and the tri-stable logical stochastic resonance model is described as:

[0039]

[0040] In the formula, β is the bias coefficient; I(t)=I 1 (t)+I 2 (t) is the two-way logic input signal I 1 (t) and I 2 (t) mixed signal; ξ(t) is additive white Gaussian noise with zero mean, and its autocorrelation function satisfies =2Dδ(t), where D is the noise intensity; U '(x) is the first derivative of the tristable potential well U(x), and the expression of U(x) is:

[0041] U(x)=x 2 (bx 2 -c) 2 +ax 2 =b 2 x 6 -2bcx 4 +(c 2 +a)x 2

[0042] In the formula, a, b, and c are the parameters of the tri-stable potential well. By adjusting the values ​​of a, b, and c, different shapes of tri-stable potential wells can be obtained. The shape of the tri-stable potential well includes: the depth, width and potential well the steepness of the wall.

[00...

Embodiment 2

[0045] After the tri-stable logic stochastic resonance system is built, according to step S2 of the method of the present invention, the logic operation type is set, including AND (and), OR (or), NOR (or not), XOR (exclusive or) and so on. Generate two logical input signals and one random noise, and calculate the theoretical logical output signal corresponding to the logical input signal according to the following table:

[0046]

[0047] Then, according to step S3 of the method of the present invention, the two input signals and noise are input into the tri-stable logic stochastic resonance model, and the logic success rate is used as an index to adjust the parameters of the tri-stable model to obtain optimal parameters and models. The logical success rate P is calculated as follows:

[0048]

[0049] In the formula, P i is the result of the i-th test, if the output signal of the tri-stable logic stochastic resonance model is the same as the theoretical logic output sign...

Embodiment 3

[0052] The above logical success rate is calculated as the result of multiple test statistics. In order to show the effect of the present invention more clearly, the model trained in step S3 of the present invention is used to process any two logical input signals according to step S4 of the present invention. The two input signals and one random noise are as follows Figure 4 (a), 4(b), and 4(c). In the actual logic operation, the noise and the input signal have been mixed together, that is, the input signal is noisy. The OR (or) theoretical logic output signal of two logic input signals is as follows Figure 5 (a). For the convenience of comparison, the traditional bistable logic stochastic resonance method is used to process the mixed signal of the two-way logic input signal and random noise. Bistable logic stochastic resonance is achieved by the following formula:

[0053]

[0054] In the formula, β is the bias coefficient; I(t)=I 1 (t)+I 2 (t) is the two-way log...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a three-stable logic stochastic resonance method, comprising: (1) building a three-stable logic stochastic resonance model; (2) generating two logic input signals and one random noise, and calculating according to a preset logic operation type The theoretical logic output signal corresponding to the two logic input signals; (3) Input the two logic input signals and one noise into the tristable logic stochastic resonance model, and use the logic success rate as an index to adjust the parameters of the tristable logic stochastic resonance model training, to obtain the optimal parameters and the optimal tristable logic stochastic resonance model consistent with the preset logic operation type; (4) the optimal logic stochastic resonance model can process other noise-containing logic input signals, and obtain correct logic output. The invention has the advantage of providing a non-linear method for realizing logic operation in a strong noise environment. Compared with the traditional method, the method can obtain a logic output with less noise and smoother waveform.

Description

technical field [0001] The invention relates to the field of logic realization of weak logic signals under strong noise background, in particular to a tri-stable logic stochastic resonance method. Background technique [0002] Stochastic resonance is a nonlinear phenomenon that can enhance weak signals with suitable noise. This phenomenon has been discovered and applied in various fields such as physics, information science, economic systems and signal processing. Most stochastic resonance methods enhance weak periodic sinusoidal signals. In addition, stochastic resonance can also use noise to realize the logic operation of two logic input signals containing noise, which is called logic stochastic resonance. [0003] There are two ways to realize the logic stochastic resonance, one is to adjust the intensity of the input noise, and the other is to adjust the parameters of the stochastic resonance model. For the former, this can only be achieved if the noise level of the i...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
CPCG06F2218/12
Inventor 陆思良代志家刘永斌琚斌刘方
Owner ANHUI UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com