TWO DISCRETE MEMRISTIVE CHAOTIC MAPS AND ITS DSP IMPLEMENTATION

Synthetic instruments apply the flexibility and computational capabilities of a digital signal-processing platform to synthesize a wide variety of synthetic instruments. The emphasis presented in traditional descriptions of a synthetic instrument is the architecture and the capabilities of the digital signal processing (DSP) platform and the user interfaces to the same. In this paper we highlight and discuss considerations of the signal conditioning and signal collection tasks. The focal point of the signal collection process is the analog-to-digital converter (ADC), the element that defines the precision and the bandwidth of the sampled data representation of the signal processed by the DSP platform. Analog signal conditioning prior to the ADC performs the task of limiting the input signal bandwidth and possible translation of the spectral band center. Digital signal conditioning following the ADC continues to perform the same tasks by further limiting the bandwidth of the digitized input signal as well as performing spectral translation with appropriate sample rate changes. In addition, the post conversion process can correct gain, phase, and time delay imbalances between input signal paths as well as gain and phase distortion encountered in the analog signal path. We identify and address performance constraints of existing ADCs and present a number of signal processing-based options to enhance and extend the operating regimes of the analog signal conditioning and the ADC conversion process.

A signal scaling design procedure, to obtain the best noise performance for a 16-QAM discrete multi-carrier transceiver, realized on a digital signal processing (DSP) platform, is presented. The experimental results demonstrate that under the proper scaling, the bit error rate (BER) of the multi-carrier transceiver can approach a very small value. The proposed signal scaling method can be applied to other DSP based multicarrier communications systems.

Developing and changing nonlinear function of Lorenz chaotic system, a new autonomous chaotic system is generated which contains three smooth quadratic terms of system variables and five equilibriums. The characteristics of five equilibriums are discussed and a fractal dimension is calculated. The features of chaotic system are analyzed in detail using bifurcation diagram and Lyapunov exponent. The period doubling bifurcation of the system can occus. The chaotic system is realized based on digital signal processing. Experimental result shows the effectiveness and feasibility of the theoretical analysis and verifies the behaviors of various attractors.

A discrete memristor model and its application in Hénon map

To functionally emulate the history-dependent plasticity and electromagnetic induction effects inherent in biochemical synapses, this paper proposes a heterogeneous neural network model in which Hindmarsh–Rose (HR) neurons and FitzHugh–Nagumo (FHN) neurons are coupled via a synaptic connection composed of a meminductor in series with a resistor. This architecture explicitly decouples synaptic function: the linear resistor models the instantaneous conductive pathway, while the meminductor implements the history-dependent plastic pathway. The complex firing dynamics of the coupled system are systematically investigated through bifurcation diagrams, Lyapunov exponent spectra, phase portraits, and time-series analysis. Results show that variations in synaptic coupling strength and coupling resistance can induce transitions among diverse firing patterns, including chaotic spiking, periodic bursting, and periodic–chaotic alternations. Crucially, the meminductive synapse introduces activity-dependent multistability, manifested as the coexistence of multiple firing patterns determined by its initial internal state. Phase synchronization analysis further demonstrates that adjusting the coupling resistance provides an independent control mechanism to effectively enhance or suppress synchronous firing between the two heterogeneous neurons, even under fixed coupling strength. Finally, the physical feasibility of the system is validated through successful digital implementation on a Digital Signal Processor (DSP) platform, with experimental measurements showing excellent agreement with numerical simulations. This study establishes the meminductor as a biomimetically grounded element for chemical synapse emulation and provides a dynamically rich, hardware-validated platform for neuromorphic computing and information processing.

In this paper, a chaotic circuit based on a memcapacitor and meminductor is constructed, and its dynamic equation is obtained. Then, the mathematical model is obtained by normalization, and the system is decomposed and summed by an Adomian decomposition method (ADM) algorithm. So as to study the dynamic behavior in detail, not only the equilibrium stability of the system is analyzed, but also the dynamic characteristics are analyzed by means of a Bifurcation diagram and Lyapunov exponents (Les). By analyzing the dynamic behavior of the system, some special phenomena, such as the coexistence of attractor and state transition, are found in the system. In the end, the circuit implementation of the system is implemented on a Digital Signal Processing (DSP) platform. According to the numerical simulation results of the system, it is found that the system has abundant dynamical characteristics.

In resource-constrained communication environments, important image data needs to be compressed before encrypted transmission. This paper proposes effective solutions to this issue. Firstly, a new one-dimensional discrete chaotic system model was constructed based on the logistic system and fractional structure. Through theoretical analysis combined with numerical simulation experiments, it has been proven that the proposed new system has excellent chaotic characteristics. Compared with some traditional one-dimensional chaotic systems, the new system has a wider range of chaotic parameters and stronger complexity, making it more suitable for image data encryption. Secondly, a high-compression-ratio image compression method based on improved lifting wavelet transform and a fast image encryption algorithm based on the new chaotic map are proposed. Simulation experiments and security analysis results show that the proposed image compression–encryption scheme has excellent performance and less time overhead. It has good resistance to various cryptanalysis attacks and strong robustness to noise and data loss attacks, which indicates that the proposed image compression–encryption scheme has good application potential in resource-constrained communication environments. The main contribution of this article is the design of a new chaotic system model with practical performance and the development of a new application case. The main novelty of this paper is the proposal of a fast algorithm for high compression ratio and encryption of images.

Recently, the application of memristors in chaotic systems has been extensively studied. Unfortunately, there is limited literature on the introduction of discrete memristors into chaotic maps, especially into non-classical multidimensional maps. For this reason, this paper establishes a new three-dimensional parabolic chaotic map model; in order to improve the complexity and randomness of the map, it is coupled with a square-charge-controlled discrete memristor to design a new four-dimensional memristive hyperchaotic map. Firstly, the stability of the two maps is discussed. And their dynamical properties are compared using Lyapunov exponential spectra and bifurcation diagrams. Then, the phase diagram and iteration sequence of the 4D memristive hyperchaotic map are obtained. Meanwhile, we investigate the hyperchaotic states, the transient chaos, state transfer and attractor coexistence phenomena of the four-dimensional memristive map. In particular, the special state transfer phenomenon of switching from a periodic attractor to a quasi-periodic attractor and the special coexistence phenomenon of a quasi-periodic attractor coexisting with a quasi-periodic attractor around fixed points are found, which have not been observed in other systems. Finally, the phase-track diagrams and iterative sequence diagrams of the four-dimensional memristive map are verified on a digital experimental platform, revealing its potential for practical applications.

Gradient-based non-dominated sorting genetic algorithm II (G-NSGA-II) is successful for solving multi-objective optimization problems. However, the effectiveness of gradient-based hybrid operator is influenced by the distribution of individuals in the population. In order to solve the problem, based on the framework of G-NSGA-II, we propose an improved gradient-based NSGA-II algorithm by introducing a new chaotic map model named IG-NSGA-II. In this algorithm, a new hybrid chaotic map model is first established to initialize population for keeping the diversity of the initial population. Then, the substitution operation of chaotic population candidate is introduced to maintain the diversity and uniformity of the Pareto optimal solution set. Finally, the proposed algorithm is tested on several standard test problems and compared with other algorithms. The experimental results indicate that the proposed algorithm leads to better performance results in terms of the convergence to Pareto front or the diversity of the obtained non-dominated solutions.

Real-time implementation of a recently introduced method of measurement of distortion product otoacoustic emissions (DPOAEs) for hearing assessment is presented. Development of the real-time application begins with the discretization of the DPOAE estimation algorithm in Matlab and then programming in C for final downloading onto a digital signal processor (DSP) platform. Aside from the signal processing task involved in the estimation process, the DSP platform controls a microphone/speaker system, which generates the acoustical stimuli for presentation to the ear canal and collects the acoustical responses recorded in the ear canal. The real-time results are compared with those obtained by a continuous-time off-line model of the DPOAE estimation algorithm. The developed DPOAE measurement system offers a high degree of noise immunity and a short measurement time, both of which are of importance in clinical applications of the DPOAE signals.

A generic voltage-controlled discrete memristor model and its application in chaotic map

The role of software is becoming increasingly important in the implementation of digital signal processing (DSP) applications. As this trend intensifies, and the complexity of applications escalates, we are seeing an increased need for automated tools to aid in the development of DSP software. This paper reviews the state of the art in programming language and compiler technology for DSP software implementation. In particular, we review techniques for high-level block-diagram-based modeling of DSP applications; the translation of block-diagram specifications into efficient C programs using global target-independent optimization techniques; and the compilation of C programs into streamlined machine code for programmable DSP processors using architecture-specific and retargetable back-end optimizations. We also point out important directions for further investigation.

A chaotic map model with infinite collapses in the finite region is proposed in this paper. The scheme of generating chaotic signals from this model is analyzed. Lyapunov exponents of the map calculated indicates that it has good properties of chaos. The CDMA spreading sequences produced by the model can achieve better autocorrelation and crosscorrelation characteristics than Gold sequences usually used.

A novel image steganography method using chaotic map and human visual model is presented in DCT domain. Firstly each 8×8 image block is performed Discrete Cosine Transform, then the location of image block that is embedded secret message is determined by the chaotic map. Finally the secret message is embedded adaptively in the usable middle frequency coefficient pairs judged by Just Noticeable Difference(JND). Simulation results show that the algorithm has a high capacity and a good invisibility, moreover it is robust for the common image processing like JPEG compression and cropping.

This article proposes a Distributed-control Architecture (D-CA) and an operation sequence with start-up strategies for a Digital Signal Processor (DSP)-based Solid-State Transformer (SST). Although various control techniques for SSTs have been reported in earlier studies, there is still a lack of research covering comprehensive content, including hierarchical control architectures and operation sequences with start-ups considering the implementation of DSPs. Therefore, this article addresses the following factors of SST. First, the D-CA is described for the design of the hierarchy between control boards. With the D-CA, because sub-boards are in charge of their corresponding DC-link voltage balancing control individually, the computational burden on the master board can be reduced. Second, the operation sequence of the SST system is explained based on the SST with D-CA. The step of DC-link voltage balance is considered throughout the entire operation sequence for safe driving. Furthermore, the PWM start-up strategies for a Cascade H-bridge Multilevel (CHM) converter and Dual Active Bridge (DAB) converter are proposed to prevent switching pulse errors caused by DSP operating characteristics. These start-up strategies reduce the current surges. The validity of the proposed D-CA and operation sequence with start-up strategies are verified by experimental results.