Variable neural networks for adaptive control of nonlinear systems

This paper is concerned with the adaptive control of continuous-time nonlinear dynamical systems using neural networks. A novel neural network architecture, referred to as a variable neural network, is proposed and shown to be useful in approximating the unknown nonlinearities of dynamical systems. In the variable neural networks, the number of basis functions can be either increased or decreased with time, according to specified design strategies, so that the network will not overfit or underfit the data set. Based on the Gaussian radial basis function (GRBF) variable neural network, an adaptive control scheme is presented. The location of the centers and the determination of the widths of the GRBFs in the variable neural network are analyzed to make a compromise between orthogonality and smoothness. The weight-adaptive laws developed using the Lyapunov synthesis approach guarantee the stability of the overall control scheme, even in the presence of modeling error(s). The tracking errors converge to the required accuracy through the adaptive control algorithm derived by combining the variable neural network and Lyapunov synthesis techniques. The operation of an adaptive control scheme using the variable neural network is demonstrated using two simulated example

Time-varying parametric modelling and time-dependent spectral characterisation with applications to EEG signals using multi-wavelets

A new time-varying autoregressive (TVAR) modelling approach is proposed for nonstationary signal processing and analysis, with application to EEG data modelling and power spectral estimation. In the new parametric modelling framework, the time-dependent coefficients of the TVAR model are represented using a novel multi-wavelet decomposition scheme. The time-varying modelling problem is then reduced to regression selection and parameter estimation, which can be effectively resolved by using a forward orthogonal regression algorithm. Two examples, one for an artificial signal and another for an EEG signal, are given to show the effectiveness and applicability of the new TVAR modelling method

Autonomous model protocell division driven by molecular replication

The coupling of compartmentalisation with molecular replication is thought to be crucial for the emergence of the first evolvable chemical systems. Minimal artificial replicators have been designed based on molecular recognition, inspired by the template copying of DNA, but none yet have been coupled to compartmentalisation. Here, we present an oil-in-water droplet system comprising an amphiphilic imine dissolved in chloroform that catalyses its own formation by bringing together a hydrophilic and a hydrophobic precursor, which leads to repeated droplet division. We demonstrate that the presence of the amphiphilic replicator, by lowering the interfacial tension between droplets of the reaction mixture and the aqueous phase, causes them to divide. Periodic sampling by a droplet-robot demonstrates that the extent of fission is increased as the reaction progresses, producing more compartments with increased self-replication. This bridges a divide, showing how replication at the molecular level can be used to drive macroscale droplet fission

A novel implementation of perturbation technique for better integration of NUTL with periodic geometry

In this work, a novel implementation of the perturbative technique (PT) recently proposed in [1] for the solution of nonuniform transmission-lines (NUTLs) is presented. Unlike the original PT, the proposed method provides a 2n-port Sparameter representation of the NUTL under analysis, which can be afterwards used in combination with different terminal conditions and/or cascaded with other 2n-port networks. As an application example, an interdigital tabbed microstrip line terminated in SMA connectors and involving a bend discontinuity is solved by the proposed technique. The obtained predictions are validated versus those provided by a full-wave solver

Resonant scattering on impurities in the Quantum Hall Effect

We develop a new approach to carrier transport between the edge states via resonant scattering on impurities, which is applicable both for short and long range impurities. A detailed analysis of resonant scattering on a single impurity is performed. The results are used for study of the inter-edge transport by multiple resonant hopping via different impurities' sites. It is shown that the total conductance can be found from an effective Schroedinger equation with constant diagonal matrix elements in the Hamiltonian, where the complex non-diagonal matrix elements are the amplitudes of a carrier hopping between different impurities. It is explicitly demonstrated how the complex phase leads to Aharonov-Bohm oscillations in the total conductance. Neglecting the contribution of self-crossing resonant-percolation trajectories, one finds that the inter-edge carrier transport is similar to propagation in one-dimensional system with off-diagonal disorder. We demonstrated that each Landau band has an extended state $\bar E_N$, while all other states are localized. The localization length behaves as $L_N^{-1}(E)\sim (E-\bar E_N)^2$.Comment: RevTex 41 pages; 3 Postscript figure on request; Final version accepted for publication in Phys. Rev. B. A new section added contained a comparison with other method

Solar radiation forecasting using ad-hoc time series preprocessing and neural networks

In this paper, we present an application of neural networks in the renewable energy domain. We have developed a methodology for the daily prediction of global solar radiation on a horizontal surface. We use an ad-hoc time series preprocessing and a Multi-Layer Perceptron (MLP) in order to predict solar radiation at daily horizon. First results are promising with nRMSE < 21% and RMSE < 998 Wh/m2. Our optimized MLP presents prediction similar to or even better than conventional methods such as ARIMA techniques, Bayesian inference, Markov chains and k-Nearest-Neighbors approximators. Moreover we found that our data preprocessing approach can reduce significantly forecasting errors.Comment: 14 pages, 8 figures, 2009 International Conference on Intelligent Computin

A New Treatment of 2N and 3N Bound States in Three Dimensions

The direct treatment of the Faddeev equation for the three-boson system in 3 dimensions is generalized to nucleons. The one Faddeev equation for identical bosons is replaced by a strictly finite set of coupled equations for scalar functions which depend only on 3 variables. The spin-momentum dependence occurring as scalar products in 2N and 3N forces accompanied by scalar functions is supplemented by a corresponding expansion of the Faddeev amplitudes. After removing the spin degrees of freedom by suitable operations only scalar expressions depending on momenta remain. The corresponding steps are performed for the deuteron leading to two coupled equations.Comment: 19 page

Array comparative genomic hybridization screening in IVF significantly reduces number of embryos available for cryopreservation

Objective During IVF, non-transferred embryos are usually selected for cryopreservation on the basis of morphological criteria. This investigation evaluated an application for array comparative genomic hybridization (aCGH) in assessment of surplus embryos prior to cryopreservation. Methods First-time IVF patients undergoing elective single embryo transfer and having at least one extra non-transferred embryo suitable for cryopreservation were offered enrollment in the study. Patients were randomized into two groups: Patients in group A (n=55) had embryos assessed first by morphology and then by aCGH, performed on cells obtained from trophectoderm biopsy on post-fertilization day 5. Only euploid embryos were designated for cryopreservation. Patients in group B (n=48) had embryos assessed by morphology alone, with only good morphology embryos considered suitable for cryopreservation. Results Among biopsied embryos in group A (n=425), euploidy was confirmed in 226 (53.1%). After fresh single embryo transfer, 64 (28.3%) surplus euploid embryos were cryopreserved for 51 patients (92.7%). In group B, 389 good morphology blastocysts were identified and a single top quality blastocyst was selected for fresh transfer. All group B patients (48/48) had at least one blastocyst remaining for cryopreservation. A total of 157 (40.4%) blastocysts were frozen in this group, a significantly larger proportion than was cryopreserved in group A (p=0.017, by chi-squared analysis). Conclusion While aCGH and subsequent frozen embryo transfer are currently used to screen embryos, this is the first investigation to quantify the impact of aCGH specifically on embryo cryopreservation. Incorporation of aCGH screening significantly reduced the total number of cryopreserved blastocysts compared to when suitability for freezing was determined by morphology only. IVF patients should be counseled that the benefits of aCGH screening will likely come at the cost of sharply limiting the number of surplus embryos available for cryopreservation

Effect of Nyquist Noise on the Nyquist Dephasing Rate in 2d Electron Systems

We measure the effect of externally applied broadband Nyquist noise on the intrinsic Nyquist dephasing rate of electrons in a two-dimensional electron gas at low temperatures. Within the measurement error, the phase coherence time is unaffected by the externally applied Nyquist noise, including applied noise temperatures of up to 300 K. The amplitude of the applied Nyquist noise from 100 MHz to 10 GHz is quantitatively determined in the same experiment using a microwave network analyzer.Comment: 5 pages, 4 figures. Author affiliation clarified; acknowledgements modified. Replacement reason clarifie