Diluted neural networks with continuous neurons and nonmonotonic transfer function are studied, with both fixed and dynamic synapses. A noisy stimulus with periodic variance results in a mechanism for controlling chaos in neural systems with fixed synapses: a proper amount of external perturbation forces the system to behave periodically with the same period as the stimulus.

Chaos is a kind of nonlinear system response that has a dense set of unstable periodic orbits (UPOs) embedded in a chaotic attractor. The idea of the chaos control is to explore the UPO stabilization obtaining dynamical systems that may quickly react to some new situation, changing conditions and their response. The OGY (Ott-GrebogiYorke) method achieves system stabilization by using small pert...

The complex Hopfield neural network (CHNN)[1,2], which is an extension of the Hopfield Neural Network from real number domain to complex number domain, exhibits both fixed point and oscillatory behavior. It may be used as an associative memory in which patterns are stored as stable oscillations. Perfect retrieval is observed when only a single pattern is stored. However, when multiple patterns ...

We study chaotic maps with multiple coexisting strange attractors and show how such systems can be controlled. To this end, a control scheme is proposed which is capable of stabilizing a desired motion within one strange attractor as well as taking the system dynamics from one strange attractor to another. To demonstrate the given control scheme, several examples are considered.

Model calculations indicate that chaotic current oscillations during anodic electrodissolution of copper into phosphoric acid may be controlled by applying a simple map-based algorithm. In the experiments, the unstable period-one and period-two orbits embedded in the chaotic attractor have been stabilized by small perturbations of the anodic potential. We present the results of an experimental ...

Control and synchronization of chaotic systems are important issues in nonlinear sciences. This paper proposes an effective estimation of distribution algorithm (EDA)-based memetic algorithm (MA) to direct the orbits of discrete chaotic dynamical systems as well as to synchronize chaotic systems, which could be formulated as complex multi-modal numerical optimization problems. In EDA-based MA (...

Chaos is a special feature of complex parametric nonlinear dynamical systems. It has the random-like behavior usually seen in stochastic systems although it is associated with deterministic dynamics. Chaos is at the edge of stability and therefore could easily lead systems to an unstable, performance-degraded, or even catastrophic situation. In such cases, chaos is considered as undesired and s...

During adolescence, prefrontal cortex regions, important in cognitive control, undergo maturation to adapt to changing environmental demands. Ways through which social-ecological factors contribute to adolescent neural cognitive control have not been thoroughly examined. We hypothesize that household chaos is a context that may modulate the associations among parental control, adolescent neural...

This paper schemes a new nonlinear method for controlling and suppressing of chaos instability in the PMSM. First, model PMSM is considered that able to describe dynamic behaviour different functional conditions, including occurrence chaos. As an integral part most physical systems, disturbance with unknown upper limit design control scheme. Parametric uncertainty also included system technique...

We propose a methodology to address the outstanding problem of synchronization in nonhyperbolic hyperchaotic physical systems. Our approach makes use of a controlling-chaos strategy that accomplishes the task by transmitting only one scalar signal even in the presence of noise.