typically, two configurations are used for energy harvesting, with different advantages: piezoelastic and piezomagnetoelastic. best performance of piezoelastic configuration is limited to its narrow bandwidth around the resonance frequency. if the excitation frequency slightly deviates from the resonance frequency, the power-out is severely reduced. to overcome this, the piezomagnetoelastic has...

This dissertation describes a methodology for solving convex constraint problems using analog circuits. It demonstrates how this methodology can be used to design circuits that solve function-fitting problems through iterated gradient descent. In particular, it shows how to build a small circuit that can model a nonlinearity by observation, and predistort to compensate for this nonlinearity. Th...

We provide a signal modality analysis to characterize and detect nonlinearity schemes in the US Industrial Production Index time series. The analysis is achieved by using the recently proposed ’delay vector variance’ (DVV) method, which examines local predictability of a signal in the phase space to detect the presence of determinism and nonlinearity in a time series. Optimal embedding paramete...

Distributed wireless sensor networks have been proposed as a solution to environment sensing, target tracking, data collection and other applications. Energy efficiency, high estimation accuracy, and fast convergence are important goals in distributed estimation algorithms for sensor network. This paper studies the problem of robust adaptive estimation in impulsive noise environment using robus...

We report the first experimental observation of nonlinear self-trapping of Bose-condensed 87Rb atoms in a one-dimensional waveguide with a superimposed deep periodic potential . The trapping effect is confirmed directly by imaging the atomic spatial distribution. Increasing the nonlinearity we move the system from the diffusive regime, characterized by an expansion of the condensate, to the non...

Neurons often integrate information from multiple parallel signaling streams. How a neuron combines these inputs largely determines its computational role in signal processing. Experimental assessment of neuronal signal integration, however, is often confounded by cell-intrinsic nonlinear processes that arise after signal integration has taken place. To overcome this problem and determine how g...

The nonlinear interactions between discrete optical solitons that propagate in different regimes of diffraction, and the nonlinear scattering of dispersive waves by local optical potentials, were studied experimentally. It is well known in electromagnetism that when linear coherentwavesmeet they interferewithout interactions. Linearwaves also scatter through local optical structureswithout exch...

The paper considers the development of a new type of artificial neural network and its applicability to non-linear system identification. This is the functional-link neural network with internal dynamic elements. The net consists of a single layer where the nonlinearity is firstly introduced by enhancing the input pattern with a functional expansion. The internal dynamic elements are auto-regre...