AIMC Topic: Nonlinear Dynamics

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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data.

Scientific reports
Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machin...

Synchronization of chaotic neural networks with time delay via distributed delayed impulsive control.

Neural networks : the official journal of the International Neural Network Society
This letter investigates the impulsive synchronization of chaotic neural networks with time delays. A novel impulsive delayed inequality is proposed, where the control effect of distributed delayed impulses is fully considered. Based on the inequalit...

Depth with nonlinearity creates no bad local minima in ResNets.

Neural networks : the official journal of the International Neural Network Society
In this paper, we prove that depth with nonlinearity creates no bad local minima in a type of arbitrarily deep ResNets with arbitrary nonlinear activation functions, in the sense that the values of all local minima are no worse than the global minimu...

Adaptive Reinforcement Learning Neural Network Control for Uncertain Nonlinear System With Input Saturation.

IEEE transactions on cybernetics
In this paper, an adaptive neural network (NN) control problem is investigated for discrete-time nonlinear systems with input saturation. Radial-basis-function (RBF) NNs, including critic NNs and action NNs, are employed to approximate the utility fu...

Observer-based sliding mode control for synchronization of delayed chaotic neural networks with unknown disturbance.

Neural networks : the official journal of the International Neural Network Society
This paper considers the synchronization of delayed chaotic neural networks with unknown disturbance via observer-based sliding mode control. We design a sliding surface involving integral structure and a discontinuous control law such that the traje...

Non-Linear Dynamical Analysis of Resting Tremor for Demand-Driven Deep Brain Stimulation.

Sensors (Basel, Switzerland)
Parkinson's Disease (PD) is currently the second most common neurodegenerative disease. One of the most characteristic symptoms of PD is resting tremor. Local Field Potentials (LFPs) have been widely studied to investigate deviations from the typical...

Robust manifold broad learning system for large-scale noisy chaotic time series prediction: A perturbation perspective.

Neural networks : the official journal of the International Neural Network Society
Noises and outliers commonly exist in dynamical systems because of sensor disturbations or extreme dynamics. Thus, the robustness and generalization capacity are of vital importance for system modeling. In this paper, the robust manifold broad learni...

Closed-loop control of nonlinear neural networks: The estimate of control time and energy cost.

Neural networks : the official journal of the International Neural Network Society
This paper concentrates on an estimate of the upper bounds for control time and energy cost of a class of nonlinear neural networks (NNs). By constructing the appropriate closed-loop controller u and utilizing the inequality technique, sufficient con...

Approximate neural optimal control with reinforcement learning for a torsional pendulum device.

Neural networks : the official journal of the International Neural Network Society
A torsional pendulum device containing hyperbolic tangent input nonlinearities can be formulated as a nonaffine system. Unlike basic affine systems, the optimal feedback control of complex nonaffine plants is difficult but quite important. In this pa...

Gene shaving using a sensitivity analysis of kernel based machine learning approach, with applications to cancer data.

PloS one
BACKGROUND: Gene shaving (GS) is an essential and challenging tools for biomedical researchers due to the large number of genes in human genome and the complex nature of biological networks. Most GS methods are not applicable to non-linear and multi-...