In this paper, a new circuit of a generator that realizes chaotic behavior is presented. This oscillator-circuit contains four resistors, two capacitors, one inductor, one diode, one operational amplifier and one voltage source. The proposed circuit was modeled by utilizing NI’s MultiSim software environment. The system’s behavior was investigated through numerical simulations, by using well-known tools of nonlinear theory, such as phase portrait, chaotic attractor and time distributions of two chaotic system-variables. This proposed circuit of chaotic generator can be used as a main part of modern systems transmitting and receiving information for masking and decryption of an information carrier.

In this paper, we investigated a three-dimensional chaotic system that models key aspects of a monetary system, including interest rates, investment demand, and price levels. The proposed system is described by a set of autonomous quadratic ordinary differential equations. We analyze the dynamic behavior of this system through equilibrium points and their stability, Lyapunov exponents (LEs), and bifurcation diagrams. The system demonstrates a variety of behaviors, including chaotic, periodic, and equilibrium states depending on parameter values. Additionally, we explore the multistability of the system and present a radial basis function neural network (RBFNN) controller design to stabilize the chaotic behavior. The effectiveness of the controller is validated through numerical simulations, highlighting its potential applications in economic and financial modeling.

It is common knowledge that nature exhibits nonlinear behavior, generally. As a result, non-linear phenomena play a vital role in the control systems in terms of engineering. That is the main reason for considering teaching nonlinear circuits in science and engineering undergraduate programs. In this paper, we present a well-known system that exhibits chaotic behavior. We quote the state equations and mathematical analysis of the Lorenz system. Afterward, we demonstrate simulation results to study and analyze the dynamic behavior of the overall system. The examples indicate a variety of ways in which chaotic behavior can arise in electronic circuits. Finally, we introduce an Arduino-based implementation of the Lorenz system. The comparison between the simulation and experimental results indicates the chaotic dynamics of the system.