AIMC Topic: Nonlinear Dynamics

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Nonlinear Semi-Supervised Metric Learning Via Multiple Kernels and Local Topology.

International journal of neural systems
Changing the metric on the data may change the data distribution, hence a good distance metric can promote the performance of learning algorithm. In this paper, we address the semi-supervised distance metric learning (ML) problem to obtain the best n...

Adaptive fuzzy sliding control of single-phase PV grid-connected inverter.

PloS one
In this paper, an adaptive fuzzy sliding mode controller is proposed to control a two-stage single-phase photovoltaic (PV) grid-connected inverter. Two key technologies are discussed in the presented PV system. An incremental conductance method with ...

The combination of circle topology and leaky integrator neurons remarkably improves the performance of echo state network on time series prediction.

PloS one
Recently, echo state network (ESN) has attracted a great deal of attention due to its high accuracy and efficient learning performance. Compared with the traditional random structure and classical sigmoid units, simple circle topology and leaky integ...

Adaptive Neural Network Control of a Robotic Manipulator With Time-Varying Output Constraints.

IEEE transactions on cybernetics
The control problem of an uncertain n -degrees of freedom robotic manipulator subjected to time-varying output constraints is investigated in this paper. We describe the rigid robotic manipulator system as a multi-input and multi-output nonlinear sys...

Classification of caesarean section and normal vaginal deliveries using foetal heart rate signals and advanced machine learning algorithms.

Biomedical engineering online
BACKGROUND: Visual inspection of cardiotocography traces by obstetricians and midwives is the gold standard for monitoring the wellbeing of the foetus during antenatal care. However, inter- and intra-observer variability is high with only a 30% posit...

Extracting T-S Fuzzy Models Using the Cuckoo Search Algorithm.

Computational intelligence and neuroscience
A new method called cuckoo search (CS) is used to extract and learn the Takagi-Sugeno (T-S) fuzzy model. In the proposed method, the particle or cuckoo of CS is formed by the structure of rules in terms of number and selected rules, the antecedent, a...

Decision-making neural circuits mediating social behaviors : An attractor network model.

Journal of computational neuroscience
We propose a mathematical model of a continuous attractor network that controls social behaviors. The model is examined with bifurcation analysis and computer simulations. The results show that the model exhibits stable steady states and thresholds f...

Time-Varying System Identification Using an Ultra-Orthogonal Forward Regression and Multiwavelet Basis Functions With Applications to EEG.

IEEE transactions on neural networks and learning systems
A new parametric approach is proposed for nonlinear and nonstationary system identification based on a time-varying nonlinear autoregressive with exogenous input (TV-NARX) model. The TV coefficients of the TV-NARX model are expanded using multiwavele...

Exponential Stabilization of Memristive Neural Networks via Saturating Sampled-Data Control.

IEEE transactions on cybernetics
This paper is concerned with the exponential stabilization of memristive neural networks (MNNs) by taking into account the sampled-data control and actuator saturation. On the one hand, the MNNs are converted into a tractable model by defining a clas...

Adaptive near-optimal neuro controller for continuous-time nonaffine nonlinear systems with constrained input.

Neural networks : the official journal of the International Neural Network Society
In this paper, an identifier-critic structure is introduced to find an online near-optimal controller for continuous-time nonaffine nonlinear systems having saturated control signal. By employing two Neural Networks (NNs), the solution of Hamilton-Ja...