Parameter identification for discrete memristive chaotic map using adaptive differential evolution algorithm

Peng, Yuexi; He, Shaobo; Sun, Kehui

doi:10.1007/s11071-021-06993-0

Cited by 53 publications

(32 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To prove the performance of the proposed SPSSA, we select five benchmark functions, which have been widely used to test the effectiveness of the SI algorithm [23]. Table 1 shows the name, range, and the minimum value of the benchmark test function.…”

Section: Benchmark Function Comparison Experimentsmentioning

confidence: 99%

“…At present, many research results have emerged for some classical continuous memristive chaotic systems, such as particle swarm optimization algorithm [14,15], differential evolution algorithm [16,17], artificial bee colony optimization algorithm [18], bird swarm algorithm [19], Jaya algorithm [20]. For a discrete memristive chaotic system, the swarm intelligence optimization algorithms also provide many practical solutions, such as an improved PSO algorithm [21], meta-heuristic algorithm [22], and enhanced differential evolution algorithm [23].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Parameter Identification for Memristive Chaotic System Using Modified Sparrow Search Algorithm

Xiong

Shen²,

Bing³

et al. 2022

Front. Phys.

View full text Add to dashboard Cite

A memristor is a non-linear element. The chaotic system constructed by it can improve its unpredictability and complexity. Parameter identification of a memristive chaotic system is the primary task to implement chaos control and synchronization. To identify the unknown parameters accurately and quickly, we introduce the Sine Pareto Sparrow Search Algorithm (SPSSA), a modified sparrow search algorithm (SSA). in this research. Firstly, we introduce the Pareto distribution to alter the scroungers’ location in the SSA. Secondly, we use a sine-cosine strategy to improve the producers’ position update. These measures can effectively accelerate the convergence speed and avoid local optimization. Thirdly, the SPSSA is used to identify the parameters of a memristive chaotic system. The proposed SPSSA exceeds the classic SSA, particle swarm optimization algorithm (PSO), and artificial bee colony algorithm (ABC) in simulations based on the five benchmark functions. The simulation results of parameter identification of a memristive chaotic system show that the method is feasible, and the algorithm has a fast convergence speed and high estimation accuracy.

show abstract

Section: Benchmark Function Comparison Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Parameter Identification for Memristive Chaotic System Using Modified Sparrow Search Algorithm

Xiong

Shen²,

Bing³

et al. 2022

Front. Phys.

View full text Add to dashboard Cite

show abstract

“…The developments of memristor materials [21,22], models [23][24][25][26], and the circuit realize based on memristor [7][8][9] have promoted the development of memristive memory technology. There are two main designs to realize memristive memory.…”

Section: Introductionmentioning

confidence: 99%

A multi-value 3D crossbar array nonvolatile memory based on pure memristors

Sun

Kang

Sun

et al. 2022

Eur. Phys. J. Spec. Top.

View full text Add to dashboard Cite

How to improve the storage density and solve the sneak path current problem has become the key to the design of nonvolatile memristive memory. In this paper, a high storage density and high reading/writing speed 3D crossbar array non-volatile memory based on pure memristors is proposed. The main works are as follows: 1) an extensible memristive cluster is proposed, 2) a memristive switch is designed, and 3) a 3D crossbar array non-volatile memory is constructed. The memory cell of the 3D crossbar array non-volatile memory is constructed by pure memristors and can be extended by adding memristor in a memristive cluster or adding memristive clusters in a memory cell to realize multi-value storage. The memristive switch can effectively reduce the sneak path current effect. The pure memristive memory cell solves the conflict between the storage density and sneak path current effect, greatly improve the storage density of memory cells. Furthermore, the 3D cross-array structure allows different memory cells on the same layer or different layers to be read and written in parallel, which greatly improves the speed of reading and writing. Simulations with PSpice verifies that the proposed memristive cluster can realize stable multi-value storage, has higher storage density, faster reading and writing speed, fewer input ports and output ports, better stability, and lower power consumption. Moreover, the structure proposed in this paper can also be used in the circuit design of the neuromorphic network, logic circuit, and other memristive circuits.

show abstract

“…The invention of the memristor has further stimulated researchers' interest in the application of chaotic systems. Numerous memristive chaotic systems have so far been introduced [4][5][6]. The most notable distinction between memristive chaotic systems and conventional dynamical systems is that the former's long-term dynamical behavior heavily depends on the memristor's initial state, which results in the dynamic phenomenon of coexisting attractors [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

A novel image encryption scheme based on memristive chaotic system and combining bidirectional bit-level cyclic shift and dynamic DNA-level diffusion

et al. 2022

View full text Add to dashboard Cite

In recent years, many researchers have leveraged various memristors to design many novel memristive chaotic systems with complex dynamics. Compared with other chaotic systems, applying these memristive chaotic systems to image encryption is expected to solve some key problems in this field. Therefore, exploiting a recently reported memristive chaotic system, this paper proposes a novel image encryption scheme based on the memristive chaotic system and combining bidirectional bit-level cyclic shift and dynamic DNA-level diffusion (IES-M-BD). First, a discrete memristive chaotic map is employed to generate chaotic sequences. Then, the plaintext image is shifted circularly on bit-level according to chaotic sequences and the hash value of the plaintext image. After that, the shifted matrix is recombined on the bit plane and encoded dynamically by DNA encoding rules. Next, dynamic DNA-level diffusion and DNA-level permutation are carried out in two rounds. Finally, the encrypted image is obtained after dynamic DNA decoding. Simulation tests and performance analyses are also carried out in this paper. The simulation results and the security analyses demonstrate that this encryption scheme has a high security level and can resist various attacks.

show abstract

Parameter identification for discrete memristive chaotic map using adaptive differential evolution algorithm

Cited by 53 publications

References 49 publications

Parameter Identification for Memristive Chaotic System Using Modified Sparrow Search Algorithm

Parameter Identification for Memristive Chaotic System Using Modified Sparrow Search Algorithm

A multi-value 3D crossbar array nonvolatile memory based on pure memristors

A novel image encryption scheme based on memristive chaotic system and combining bidirectional bit-level cyclic shift and dynamic DNA-level diffusion

Contact Info

Product

Resources

About