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Aiming at the problem that speech information has a strong correlation in adjacent times and the data type is floating point, the image encryption algorithm of integer type is not suitable for speech encryption. This paper proposed a speech encryption algorithm based on robust chaotic mapping, which mainly utilizes the nonlinearities and dynamics of robust chaos to adapt to the characteristics of speech signals. Furthermore, a new 3D sine robust chaotic mapping (3D-SRCM) model is proposed in this paper, which effectively solves the problems of discontinuous parameter ranges, prone to chaotic degradation and lack of robustness in existing chaotic systems, and improves the robustness and complexity of chaos. In the speech encryption algorithm, the parameters of the chaotic mapping are adjusted according to the changes in speech signal characteristics to generate unique keys for different speech signals. The encryption algorithm compresses and denoises the signal through the Fast Walsh–Hadamard Transform (FWHT) before using chaotic sequences for initial scrambling encryption. Then, the signal is transformed by Discrete Wavelet Transform (DWT) to realize the second round of scrambling and diffusion encryption. This structure increases the security of the encryption algorithm and ensures the efficiency and reliability of the encryption process. The experimental results show that the algorithm has a large key space, good resistance to exhaustive attack, and statistical attack, which can effectively resist chosen plaintext attack. In the decryption process, the algorithm can quickly and accurately decrypt the encrypted speech with good decryption performance. • A speech encryption algorithm based on robust chaos was proposed. • A new 3D-SRCM model is proposed for existing chaotic systems. • The 3D-SRCM model solves chaotic degradation, improving robustness and complexity. • Control parameters were adjusted to adapt to speech signal, linking key and the signal. • In the encryption algorithm, the parameters of the chaotic map are adjusted to fit the speech signal. [ABSTRACT FROM AUTHOR]

We study two-dimensional, two-piece, piecewise-linear maps having two saddle fixed points. Such maps reduce to a four-parameter family and are well known to have a chaotic attractor throughout open regions of parameter space. The purpose of this paper is to determine where and how this attractor undergoes bifurcations. We explore the bifurcation structure numerically by using Eckstein's greatest common divisor algorithm to estimate from sample orbits the number of connected components in the attractor. Where the map is orientation-preserving the numerical results agree with formal results obtained previously through renormalisation. Where the map is orientation-reversing or non-invertible the same renormalisation scheme appears to generate the bifurcation boundaries, but here we need to account for the possibility of some stable low-period solutions. Also the attractor can be destroyed in novel heteroclinic bifurcations (boundary crises) that do not correspond to simple algebraic constraints on the parameters. Overall the results reveal a broadly similar component-doubling bifurcation structure in the orientation-reversing and non-invertible settings, but with some additional complexities. [ABSTRACT FROM AUTHOR]

We consider a family of one-dimensional continuous piecewise smooth maps with monotone increasing and monotone decreasing branches. It is associated with a credit cycle model introduced by Matsuyama, under the assumption of the Cobb-Douglas production function. We offer a detailed analysis of the dynamics of this family. In particular, using the skew tent map as a border collision normal form we obtain the conditions of abrupt transition from an attracting fixed point to an attracting cycle or a chaotic attractor (cyclic chaotic intervals). These conditions allow us to describe the bifurcation structure of the parameter space of the map in a neighborhood of the boundary related to the border collision bifurcation of the fixed point. Particular attention is devoted to codimension-two bifurcation points. Moreover, the described bifurcation structure confirms that the chaotic attractors of the considered map are robust, that is, persistent under parameter perturbations. [ABSTRACT FROM AUTHOR]

Suspended beam micro/nanoelectromechanical (MEMS/NEMS) resonators are relevant potential sources of chaotic signals for many practical applications due to their low power consumption and high operating frequencies. However, chaos is generally restricted to small regions of the parameter space when MEMS/NEMS resonators are driven by a single frequency, as considered so far in most of the literature and all experiments. It has recently been found that strong chaotification and robust chaos (characterized by a chaotic attractor insensitive to changes on the system parameters) can emerge in the resonators when excited by two distinct frequencies. Here we show that this strong chaotification not only increases the regions in the parameter space with chaos, but also enhances the complexity of the chaotic dynamics. These findings make MEMS/NEMS resonators even more attractive for practical applications. The increase in complexity is demonstrated through the analysis of the Fourier spectrum and the use of recurrence quantification analysis (RQA). A larger entropy of the Fourier spectrum and lower determinism are obtained compared to the single frequency excitation as the amplitude of the second frequency increases. • Large chaotification of the system is observed under two-frequency excitation. • The complexity of the chaotic dynamics for two-frequency excitation is investigated. • The complexity increases as the amplitude of the second frequency is increased. [ABSTRACT FROM AUTHOR]

Abstract: When dealing with piecewise-smooth systems, the chaotic domain often does not contain any periodic inclusions, which is called “robust chaos”. Recently, the bifurcation structures in the robust chaotic domain of 1D piecewise-linear maps were investigated. It was shown that several regions of multi-band chaotic attractors emerge at the boundary between the periodic and the chaotic domain, forming complex self-similar bifurcation structures. However, some multi-band regions were observed also far away from this boundary. In this work we consider the question how these regions emerge and how they become disconnected from the boundary. [Copyright &y& Elsevier]