AIMC Topic:
Computer Simulation

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Pre-Synaptic Pool Modification (PSPM): A supervised learning procedure for recurrent spiking neural networks.

PloS one
Learning synaptic weights of spiking neural network (SNN) models that can reproduce target spike trains from provided neural firing data is a central problem in computational neuroscience and spike-based computing. The discovery of the optimal weight...

Using isotopic envelopes and neural decision tree-based in silico fractionation for biomolecule classification.

Analytica chimica acta
Untargeted mass spectrometry (MS) workflows are more suitable than targeted workflows for high throughput characterization of complex biological samples. However, analysis workflows for untargeted methods are inadequate for characterization of comple...

Numerosity discrimination in deep neural networks: Initial competence, developmental refinement and experience statistics.

Developmental science
Both humans and non-human animals exhibit sensitivity to the approximate number of items in a visual array, as indexed by their performance in numerosity discrimination tasks, and even neonates can detect changes in numerosity. These findings are oft...

Adaptive tracking control of an unmanned aerial system based on a dynamic neural-fuzzy disturbance estimator.

ISA transactions
The main goal of this study is developing an adaptive controller which can solve the trajectory tracking for a class of quadcopter unmanned aerial system (UAS), namely a quadrotor. The control design introduces a new paradigm for adaptive controllers...

Reachable set bounding for neural networks with mixed delays: Reciprocally convex approach.

Neural networks : the official journal of the International Neural Network Society
This paper discusses the reachable set estimation problem of neural networks with mixed delays. Firstly, by means of the maximal Lyapunov-Krasovskii functional, we obtain a non-ellipsoid form of the reachable set. Further more, when calculating the d...

Multiperspective Light Field Reconstruction Method via Transfer Reinforcement Learning.

Computational intelligence and neuroscience
Compared with traditional imaging, the light field contains more comprehensive image information and higher image quality. However, the available data for light field reconstruction are limited, and the repeated calculation of data seriously affects ...

Coding with transient trajectories in recurrent neural networks.

PLoS computational biology
Following a stimulus, the neural response typically strongly varies in time and across neurons before settling to a steady-state. While classical population coding theory disregards the temporal dimension, recent works have argued that trajectories o...

Dynamic Modeling and Simulation of a Body Weight Support System.

Journal of healthcare engineering
This paper proposes a body weight support (BWS) system with a series elastic actuator (SEA) to facilitate walking assistance and motor relearning during gait rehabilitation. This system comprises the following: a mobile platform that ensures movement...

A Machine Learning Approach for Drug-target Interaction Prediction using Wrapper Feature Selection and Class Balancing.

Molecular informatics
Drug-Target interaction (DTI) plays a crucial role in drug discovery, drug repositioning and understanding the drug side effects which helps to identify new therapeutic profiles for various diseases. However, the exponential growth in the genomic and...

Machine Learning for Cancer Drug Combination.

Clinical pharmacology and therapeutics
When treating multiple complex diseases, such as cancer, polytherapy may demonstrate efficiency than monotherapy. However, due to the multiplicative relationship between the number of drugs and cell lines vs. the number of combinations, it is impract...