AIMC Topic: Nonlinear Dynamics

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A novel fractional-order memristive Hopfield neural network for traveling salesman problem and its FPGA implementation.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a novel fractional-order memristive Hopfield neural network (HNN) to address traveling salesman problem (TSP). Fractional-order memristive HNN can efficiently converge to a globally optimal solution, while conventional HNN tends t...

Lag projective synchronization of discrete-time fractional-order quaternion-valued neural networks with time delays.

Neural networks : the official journal of the International Neural Network Society
This paper deals with the lag projective synchronization (LPS) problem for a class of discrete-time fractional-order quaternion-valued neural networks(DTFO QVNNs) systems with time delays. Firstly, a DTFOQVNNs system with time delay is constructed. S...

A Least-Square Unified Framework for Spatial Filtering in SSVEP-Based BCIs.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The steady-state visual evoked potential (SSVEP) has become one of the most prominent BCI paradigms with high information transfer rate, and has been widely applied in rehabilitation and assistive applications. This paper proposes a least-square (LS)...

pyDarwin machine learning algorithms application and comparison in nonlinear mixed-effect model selection and optimization.

Journal of pharmacokinetics and pharmacodynamics
Forward addition/backward elimination (FABE) has been the standard for population pharmacokinetic model selection (PPK) since NONMEM® was introduced. We investigated five machine learning (ML) algorithms (Genetic algorithm [GA], Gaussian process [GP]...

deepAFT: A nonlinear accelerated failure time model with artificial neural network.

Statistics in medicine
The Cox regression model or accelerated failure time regression models are often used for describing the relationship between survival outcomes and potential explanatory variables. These models assume the studied covariates are connected to the survi...

Inverse-free zeroing neural network for time-variant nonlinear optimization with manipulator applications.

Neural networks : the official journal of the International Neural Network Society
In this paper, the problem of time-variant optimization subject to nonlinear equation constraint is studied. To solve the challenging problem, methods based on the neural networks, such as zeroing neural network and gradient neural network, are commo...

Deep learning-based low-dose CT simulator for non-linear reconstruction methods.

Medical physics
BACKGROUND: Computer algorithms that simulate lower-doses computed tomography (CT) images from clinical-dose images are widely available. However, most operate in the projection domain and assume access to the reconstruction method. Access to commerc...

Nonlinear classifiers for wet-neuromorphic computing using gene regulatory neural network.

Biophysical reports
The gene regulatory network (GRN) of biological cells governs a number of key functionalities that enable them to adapt and survive through different environmental conditions. Close observation of the GRN shows that the structure and operational prin...

Adaptive neural fault-tolerant prescribed performance control of a rehabilitation exoskeleton for lower limb passive training.

ISA transactions
This article studies the passive tracking problem of a wearable exoskeleton for lower limb rehabilitation therapy in the face of unmodeled dynamics, interactive friction, disturbance, prescribed performance constraints, and actuator faults. Adaptive ...

Adaptive sampling artificial-actual control for non-zero-sum games of constrained systems.

Neural networks : the official journal of the International Neural Network Society
Considering physical constraints encountered by actuators, this paper addresses the non-zero-sum game of continuous nonlinear systems with symmetric and asymmetric input constraints through aperiodic sampling artificial-actual control. Initially, the...