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Verifies the tunneling junction that can be modeled by a piecewise linear voltage-charge relation using physics-based Monte Carlo simulations which from the circuit-theoretic perspective is a nonlinear capacitor. Physical schematics of a single-electron tunneling junction; Simulation of a current-biased single-electron tunneling junction; Simulation of a voltage-biased single-electron tunneling junction.

Presents information on a study which described a synaptic model called comparative synapse, a multiplication free approach to neuro-fuzzy classifiers. General model for synaptic operator; Performance of the comparative synapse for several benchmark classification problems; Conclusions.

Uncovers the secret mechanisms which are responsible for the self organization and spontaneous emergence of many stable complex (static and dynamic) patterns in homogeneous media operating far-from-thermodynamic equilibrium. Definition of cellular neural networks (CNN); Information on reaction-diffusion (PDE) mapping into CNN; Local activity for reaction-diffusion CNN.

Presents information on a study which proposed an approach for synthesizing a prescribed driving-point (DP) characteristics of a nonlinear resistor from the transfer characteristic (TC) of a two-port resistive element. Implementation of the TC-to-DP characteristic converter; Digital technique for synthesizing prescribed TC of two-port devices; Examples of DP characteristics synthesized by TC; Conclusions.

Provides information on the complete stability of nonsymmetric cellular neural networks (CNN). Role played by the convergence theorem of the Gauss-Seidel method, an interative technique for solving a linear algebraic equation; Use of this method to illustrate that the existence of a stable equilibrium point does not imply complete stability of a nonsymmetric CNN.

Presents a study which examines the characteristics of quantized sampling as it relates to electric circuit analysis. How time and space is treated in engineering analysis; Methods and materials used in the study; Framework of quantized sampling.

Focuses on the sufficient condition for nonsymmetric cellular neural networks (CNN's) to have a stable equilibrium point. Reason a stable equilibrium point is important to the CNN's; Application of the sufficient condition to space-invariant CNN's with a 3X3 neighborhood.

Looks at the impulsive control of chaotic systems. Presentation of theorems on the stability of impulsive control systems; Use of the theorems to find the conditions under which chaotic systems can be asymptotically controlled; Estimation of the upper bound of the impulse interval given; Theory of impulsive synchronization of two chaotic systems.

Presents information on a physical implementation of the twist-and-flip circuit containing a nonlinear gyrator. Experimental observations of the Poincare maps in the twist-and-flip circuit; Illustration of phrase portraits and their associated Poincare maps; Implementation of the twist-and-flip circuit.

Focuses on the use of adaptive controllers to maintain the synchronization of two Chua's circuits with time-varying channels and parameters. Examination of chaotic systems; Adaptive controllers for time-varying channels and time-varying compensation; Experimental results.

Extends chaotic switching to general chaotic parameter modulation. G-modulation; Transmission of signals; Circuit description.

Introduces a real-time programmable, spatial-temporal bifurcation test bed. Presentation of the experimental analysis of an antisymmetric template class; Production of spatial-temporal patterns that exhibit complex dynamics; Dependence of the characteristic of the propagating patterns on the self-feedback and on the sign of the coupling below the self-feedback template element.

Proposes a universal piecewise-linear cellular nonlinear network coupling cell, the simplicial cell, which is intended to work with binary as well as gray-level inputs. Key features of a coupling cell; Parameters of the simplicial coupling cell; Application to gray-level image processing.

Presents an extended class of synaptic operators which includes the standard multiplication as a particular case. Establishment of the properties of the extended class of operators; Information on the global stability theorem of cellular neural networks, which is applicable to the extended class of synaptic operator; Importance of the multiplier-based synapse; Effectiveness of the synaptic operator.

Describes a torus-doubling phenomenon which was observed from four mutually coupled Chua's circuits while looking at coupled oscillators. What are coupled oscillators; Details on the qualitative dynamical behavior of the coupled system; Indepth look at the numerical simulation resulting from the system model.

Introduces a structure called the simplicial cellular neural network (CNN). Use of any Boolean/Gray-level function of any number of variables; Analysis of circuit architectures for the implementation of the simplicial CNN based on resonant tunneling diodes; Application of a fully programmable CNN in a hardware platform based on nanoelectronic devices.

Proposes the development of a cellular neural network (CNN)-based morphological engine. Details on the introduction of a effective implementation method for the engine; Experimental process of the implementation method; Definition of basic morphological operations.