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Abstract: A novel chaotic spiking neuron is presented and its nonlinear dynamics and encoding functions are analyzed. A set of paralleled neurons accepts a common analog input and outputs a set of chaotic spike-trains. Three theorems which guarantee that the neurons can encode the analog input into a summation of the chaotic spike-trains are derived: (1) a spike histogram of the summed spike-train can mimic waveforms of various inputs, (2) the spike-trains do not synchronize to each other and thus the summed spike-train can have times higher encoding resolution than each single spike-train, and (3) firing rates of the neurons can be adjusted by internal parameters. The theorems are proven by using nonlinear iterative maps and are confirmed by numerical simulations as well. Electronic circuit implementation methods of the paralleled neurons are also presented and typical paralleled encoding functions are confirmed by both experimental measurements and SPICE simulations. [Copyright &y& Elsevier]

This paper studies stabilization of low-period unstable periodic orbits (UPOs) in a simplified model of a current mode H-bridge inverter. The switching of the inverter is controlled by pulse-width modulation signal depending on the sampled inductor current. The inverter can exhibit rich nonlinear phenomena including period doubling bifurcation and chaos. Our control method is realized by instantaneous opening of inductor at a zero-crossing moment of an objective UPO and can stabilize the UPO instantaneously as far as the UPO crosses zero in principle. Typical system operations can be confirmed by numerical experiments. [ABSTRACT FROM AUTHOR]

We consider quantized chaotic dynamics for a spiking oscillator with two periodic inputs. As the first input is applied, the oscillator generates various periodic and chaotic pulse-trains governed by a pulse position map. As the second input is added, the oscillator produces pulse positions restricted on a lattice, and the pulse position map is quantized. Then the oscillator generates a set of super-stable periodic pulse-trains (SSPTs). The oscillator has various coexisting SSPTs and generates one of them depending on the initial state condition. In order to characterize the set of SSPTs, we elucidate the number and the minimum pulse interval of the SSPTs theoretically. By presenting a simple test circuit, we then verify some typical phenomena in the laboratory environment. [ABSTRACT FROM AUTHOR]

Presents information on a study which considered the master-slave synchronization of a complex chaotic system using multiplex pulse trains. Design of the system; Analysis of synchronization behavior; Synchronization via multiplex and stabilized pulse trains; Conclusions.

Presents a study which proposes a network of continuous-time chaotic cells and considers its dynamics. Presentation of a cell exhibits chaos; Methods and materials used in the study; Construction of a network by occasional linear connection.

Discusses control of chaos from an artificial neural cell. Description of the cell as piecewise linear and with bipolar hysteresis; Proof of chaos generation using a mapping procedure; Calculation of the initial point of unstable periodic orbits (UPO) embedded in chaos; Stabilization of the desired UPO by using a modified occasional proportional feedback.