Modular chaotification model with FPGA implementation

作     者：HUA Zhong Yun ZHOU BingHang ZHANG YinXing ZHOU YiCong HUA ZhongYun;ZHOU BingHang;ZHANG YinXing;ZHOU YiCong

作者机构：School of Computer Science and TechnologyHarbin Institute of TechnologyShenzhenShenzhen518055China College of Electrical and Information EngineeringHunan UniversityChangsha410082China Department of Computer and Information ScienceUniversity of MacaoMacao999078China 

出 版 物：《Science China(Technological Sciences)》 (中国科学（技术科学英文版）)

年 卷 期：2021年第64卷第7期

页      面：1472-1484页

核心收录：

学科分类：080902[工学-电路与系统] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：supported by the National Natural Science Foundation of China (Grant No. 62071142) the Natural Scientific Research Innovation Foundation in Harbin Institute of Technology (Grant No. HIT.NSRIF.2020077) 

主　　题：nonlinear system chaotic system field-programmable gate array(FPGA) pseudorandom number generator(PRNG) hardware implementation 

摘      要：Chaotic systems are an effective tool for various applications, including information security and internet of things. Many chaotic systems may have the weaknesses of incomplete output distributions, discontinuous chaotic regions, and simple chaotic *** may result in many negative influences in practical applications utilizing chaos. To deal with these issues, this study introduces a modular chaotification model(MCM) to increase the dynamic properties of current one-dimensional(1 D) chaotic maps. To exhibit the effect of the MCM, three 1 D chaotic maps are improved using the MCM as examples. Studies of the resulting properties show the robust and complex dynamics of these improved chaotic maps. Moreover, we implement these improved chaotic maps of MCM in a field-programmable gate array hardware platform and apply them to the application of PRNG. Performance analyses verify that these chaotic maps improved by the MCM have more complicated chaotic behaviors and wider chaotic ranges than the existing and several new chaotic maps.