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Random number generating method and device

A technology for generating devices and random numbers, applied in random number generators, encoding/decoding devices, pulse generation with predetermined statistical distribution of parameters, etc., can solve problems such as expensive and large-scale devices, and achieve the effect of simple structure

Inactive Publication Date: 2006-12-13
NLLGATA TLO LNC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, most of these methods require expensive, large-scale setups

Method used

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  • Random number generating method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0074]

[0075] (1) When using a triangle wave

[0076]Set the output of the oscillator based on the crystal oscillator (crystal oscillator: NFCORPORATION WAVE FACTORY 1946 (NF CORPORATION WAVE FACTORY 1946)) as a triangular wave of -4.95 to +4.95V, using a 12-bit long, binary A / D The conversion performs A / D conversion on this signal, and then takes it into the computer. At this time, the sampling frequency is 1MHz. Figure 5 The relationship between the oscillation frequency of the above-mentioned oscillator and the pass rate of the test is shown in . The horizontal axis of the graph represents the oscillation frequency, and the vertical axis represents the verification pass rate. from Figure 5 It can be seen that almost 100% of tests are passed when the oscillation frequency is about 15 KHz or higher.

[0077] (2) When using a sine wave

[0078] Use the same crystal oscillator as in (1) above, and set its output as a sine wave of -4.95 to +4.95V. In addition, the sa...

Embodiment 2

[0080]

[0081] Using 12-bit long binary A / D conversion pairs from Figure 4 The output of the shot noise generation circuit shown is A / D converted and then taken into the computer. r0, r1, r2, . Use 20,000 r0 as a group, denoted as r0(20000), and 20,000 r1 as a group, denoted as r1(20000). Figure 7 , shows the relationship between the sampling frequency and the test pass rate when the sampling frequency is changed for these data series. from Figure 7 It can be seen that the more the lower bits are used, the higher the verification passing rate is maintained until the sampling frequency is high, and the lowest bit r0 is particularly remarkable.

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Abstract

It is an object of the present invention to provide, with simple and not expensive devices, a new method for generating random number with more perfectly disorder and a random number generator which is utilized in the generating method of random number. In this point of view, a noise or a signal oscillated from an oscillator is input into an A / D converter. Then, numbers of '0' and '1' are allotted at lower bit rank to output signals from the A / D converter to generate a binary random number. Then, the binary random number is divided by a given digit number to generate an n-scaled random number.

Description

technical field [0001] The invention relates to a random number generating method and a random number generating device. Background technique [0002] Random numbers that are completely disordered and have an overall equal frequency of occurrence are widely used in numerical simulations of social phenomena or physical phenomena, and the like. In addition, random numbers also play an important role as an encryption technique, so they are also in great demand in the field of information protection. Currently, various methods have been developed as methods for generating random numbers, but most of them are pseudo-random number generation based on algorithm-based software. [0003] Algorithm-based random number generation is widely used because it has a certain degree of reliability and can perform random number generation at high speed. However, since computers can only access limited information, the generated random numbers proved to be periodic. Therefore, sometimes a co...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F7/58H03K3/84G09C1/00
Inventor 齐藤义明茂吕友子
Owner NLLGATA TLO LNC