Abstract We propose and analyse a numerical integrator that computes low-rank approximation to large time-dependent matrices are either given explicitly via their increments or the unknown solution matrix differential equation. Furthermore, is extended of tensors by Tucker fixed multilinear rank. The proposed different from known projector-splitting for dynamical approximation, but it retains i...

for many physical systems like vehicles, acceleration can be easily measured for the respective states. however, the outputs are usually affected by stochastic noise disturbance. the mentioned systems are often sensitive to noise and structural uncertainties. furthermore, it is very difficult to estimate the multiple integrals of the signal, acceleration to velocity and velocity to position. in...

Black box modeling of diffusion processes can be performed by fractional models. The simulation of these particular models is based on a new fractional integrator, with limited spectral range. Parameter estimation of this class of systems is performed by an OE identification technique. This paper presents the application of this new methodology to the modeling of different diffusive systems dea...

This paper describes a new firstand second-order delta-sigma modulator concept where the first integrator is extracted and implemented by a frequency modulator with the modulating signal as the input. The result is a simple delta-sigma modulator with no need for digital-to-analog converters, allowing straight-forward multi-bit quantization. Without the frequency modulator, the circuit becomes a...

After reviewing several physiological findings on oscillations in the electroencephalogram (EEG) and their possible explanations by dynamical modeling, we present neural networks consisting of leaky integrator units as an universal paradigm for neural and cognitive modeling. In contrast to standard recurrent neural networks, leaky integrator units are described by ordinary differential equation...

This paper represents a method to improve the SNR and linearity of an integrator by feedback compensation technique. The discussed design reduces signal swing while keeping advantages of both feed-forward as well as feedback topology without changing the signal transfer function. SNR and linearity are related to the output of an integrator. Reduced SNR and non-linearity resulted because of the ...