AIMC Topic: Computer Simulation

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Networks that learn the precise timing of event sequences.

Journal of computational neuroscience
Neuronal circuits can learn and replay firing patterns evoked by sequences of sensory stimuli. After training, a brief cue can trigger a spatiotemporal pattern of neural activity similar to that evoked by a learned stimulus sequence. Network models s...

Slithering towards autonomy: a self-contained soft robotic snake platform with integrated curvature sensing.

Bioinspiration & biomimetics
Soft robotic snakes promise significant advantages in achieving traveling curvature waves with a reduced number of active segments as well as allowing for safe and adaptive interaction with the environment and human users. However, current soft robot...

Regular graphs maximize the variability of random neural networks.

Physical review. E, Statistical, nonlinear, and soft matter physics
In this work we study the dynamics of systems composed of numerous interacting elements interconnected through a random weighted directed graph, such as models of random neural networks. We develop an original theoretical approach based on a combinat...

Nonlinear Inertia Weighted Teaching-Learning-Based Optimization for Solving Global Optimization Problem.

Computational intelligence and neuroscience
Teaching-learning-based optimization (TLBO) algorithm is proposed in recent years that simulates the teaching-learning phenomenon of a classroom to effectively solve global optimization of multidimensional, linear, and nonlinear problems over continu...

Robust Integral of Neural Network and Error Sign Control of MIMO Nonlinear Systems.

IEEE transactions on neural networks and learning systems
This paper presents a novel state-feedback control scheme for the tracking control of a class of multi-input multioutput continuous-time nonlinear systems with unknown dynamics and bounded disturbances. First, the control law consisting of the robust...

Prediction of facial deformation after complete denture prosthesis using BP neural network.

Computers in biology and medicine
With the accelerated aging of world population, complete denture prosthesis plays an increasingly important role in mouth rehabilitation. In addition to recovering stomatognathic system function, restoring the appearance of a third of the area under ...

Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation.

Computational intelligence and neuroscience
An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heurist...

A Robot-Driven Computational Model for Estimating Passive Ankle Torque With Subject-Specific Adaptation.

IEEE transactions on bio-medical engineering
BACKGROUND: Robot-assisted ankle assessment could potentially be conducted using sensor-based and model-based methods. Existing ankle rehabilitation robots usually use torquemeters and multiaxis load cells for measuring joint dynamics. These measurem...

A Multiobjective Sparse Feature Learning Model for Deep Neural Networks.

IEEE transactions on neural networks and learning systems
Hierarchical deep neural networks are currently popular learning models for imitating the hierarchical architecture of human brain. Single-layer feature extractors are the bricks to build deep networks. Sparse feature learning models are popular mode...

Neural-Dynamic-Method-Based Dual-Arm CMG Scheme With Time-Varying Constraints Applied to Humanoid Robots.

IEEE transactions on neural networks and learning systems
We propose a dual-arm cyclic-motion-generation (DACMG) scheme by a neural-dynamic method, which can remedy the joint-angle-drift phenomenon of a humanoid robot. In particular, according to a neural-dynamic design method, first, a cyclic-motion perfor...