Attractor learning with nonlinear, artificial, neural network
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Short-term electrical load forecasting is a topic of major interest for the planning of energy production and distribution. The use of artificial neural networks has been demonstrated as a valid alternative to classical statistical methods in term of accur ...
FMRI time course processing is traditionally performed using linear regression followed by statistical hypothesis testing. While this analysis method is robust against noise, it relies strongly on the signal model. In this paper, we propose a non-parametri ...
The application of nuclear norm regularization to system identification was recently shown to be a useful method for identifying low order linear models. In this paper, we consider nuclear norm regularization for identification of simulated moving bed proc ...
FMRI time course processing is traditionally performed using linear regression followed by statistical hypothesis testing. While this analysis method is robust against noise, it relies strongly on the signal model. In this paper, we propose a non-parametri ...
Spie-Int Soc Optical Engineering, Po Box 10, Bellingham, Wa 98227-0010 Usa2007
The European Union (EU) has adopted directives requiring that Member States take measures to reach a “good” chemical status of water resources by the year 2015 (Water Framework Directive: WFD). In order to achieve the environmental objectives for groundwat ...
It is quite difficult to construct circuits of spiking neurons that can carry out complex computational tasks. On the other hand even randomly connected circuits of spiking neurons can in principle be used for complex computational tasks such as time-warp ...
A novel method for the detn. of partition coeffs. in aq.-org. two-phase systems is described. It is applicable for characterizing the distribution of substances undergoing proton dissocn. in the aq. phase. The method is based on titrn. by means of the org. ...
Short term electrical load forecasting is a topic of major interest for the planning of energy production and distribution. The use of artificial neural networks has been demonstrated as a valid alternative to classical statistical methods in term of accur ...
The application of nuclear norm regularization to system identification was recently shown to be a useful method for identifying low order linear models. In this paper, we consider nuclear norm regularization for identification of LTI systems with missing ...
This work evaluates three techniques of calibrating capacitance (dielectric) spectrometers used for on-line monitoring of biomass: modeling of cell properties using the theoretical Cole-Cole equation, linear regression of dual-frequency capacitance measure ...