## 1 Introduction  
So far, a significant number of research papers have been focused on numerical analysis of conventional electrical circuits from the viewpoint of chaos evolution. The general definition of chaos speaks about long-time unpredictable behavior, dense state attractors with a fractal dimension, generated waveforms with increased entropy, and extreme sensitivity to small changes in initial conditions. The mentioned properties can be detected and quantified using several well-established numerical algorithms. For example, a routine known as approximate entropy [1; 2; 3] can be used to measure self-similarity of the data sequence produced by any dynamical system. The time sequence can be used for calculation of the largest Lyapunov exponent as well; see [4; 5] for more details. More precise results of the quantification of dynamical motion can be reached if describing a mathematical model (set of ordinary differential equations) is known. Spectra of Lyapunov exponents can be also calculated using linearization of the flow along the evolved state trajectory [6; 7; 8; 9]. The same method can be utilized for optimization, i.e., to increase robustness of the chaotic operational regime [10], to find the parameter subspace leading to chaos [11] in the analyzed dynamical system, or to replace parts of chaotic oscillators without changing of global dynamics [12]. Some research papers showed the possibility to study chaotic systems via patterns of return maps [13], bifurcation diagrams associated with real circuits [14] and processes [15], etc. Some recent papers were focused on analysis and circuit design of fractional-order chaotic oscillators. These should be dealt with as systems that contain constant phase elements, as demonstrated in [16]. Chaos can be observed in various lumped electronic circuits, including standard structures of radio frequency systems. For example, the famous [PERSON]'s oscillator [17] can be considered a parallel LC oscillator loaded with a timing network and negative resistance. This mature topology still serves as an educational example of a robust chaotic system and has already undergone thorough analytical, numerical, and experimental analysis [18]. After the early discovery of [PERSON]'s system, evidence of chaos in other types of naturally harmonic oscillators was only a matter of time. The existence of strange attractors within the dynamics of the well-known Colpitts oscillator was revealed in [19]. One logical step further, namely, interchanges of network components, one can observe chaos in [PERSON]'s oscillator [20]. The process of chaofification of the common Wien bridge oscillator was a subject of an interesting paper [21; 22; 23]. It was demonstrated in a step-by-step manner that different passive feedback two-ports can be used for chaos generation. A study [24] presented the concept of a looped passive low-pass filter (arbitrary structure) and active two-port having smooth polynomial transfer characteristics. Phase-locked loops can be also subject to complex behavior, including multistability and chaos, as proved in a research paper [25]. Many power electronic systems are ideal candidates to observe chaotic solutions. Let us mention a few interesting examples, namely, the switched-mode power converter [26], DC-DC converter [27], and buck [28] and boost [29] converter. A dynamical model of multistate static memory possesses, by principle, a very complex configuration of the vector field [30]. However, its chaotic behavior was described only very recently; see papers [31; 32] for more details. Besides the papers dealing with autonomous deterministic dynamical systems mentioned above, chaos can easily evolve in the electronic circuits under periodic driving. For example, state-variable frequency filters can produce chaotic signals if two conditions are satisfied: a high-quality factor and piecewise-linear or polynomial feedback nonlinearity [33]. The same network structures can also generate robust chaos in the case of nonlinear integrators [34].