AIMC Topic: Neural Networks, Computer

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Classification of vertices on social networks by multiple approaches.

Mathematical biosciences and engineering : MBE
Due to the advent of the expressions of data other than tabular formats, the topological compositions which make samples interrelated came into prominence. Analogically, those networks can be interpreted as social connections, dataflow maps, citation...

A survey of adaptive optimal control theory.

Mathematical biosciences and engineering : MBE
This paper makes a survey about the recent development of optimal control based on adaptive dynamic programming (ADP). First of all, based on DP algorithm and reinforcement learning (RL) algorithm, the origin and development of the optimization idea ...

Research on chest radiography recognition model based on deep learning.

Mathematical biosciences and engineering : MBE
With the development of medical informatization and against the background of the spread of global epidemic, the demand for automated chest X-ray detection by medical personnel and patients continues to increase. Although the rapid development of dee...

Synchronization of fractional-order memristive recurrent neural networks via aperiodically intermittent control.

Mathematical biosciences and engineering : MBE
In this paper, synchronization of fractional-order memristive recurrent neural networks via aperiodically intermittent control is investigated. Considering the special properties of memristor neural network, differential inclusion theory is introduce...

Probing the Relationship Between Latent Linear Dynamical Systems and Low-Rank Recurrent Neural Network Models.

Neural computation
A large body of work has suggested that neural populations exhibit low-dimensional dynamics during behavior. However, there are a variety of different approaches for modeling low-dimensional neural population activity. One approach involves latent li...

Scalability of Large Neural Network Simulations via Activity Tracking With Time Asynchrony and Procedural Connectivity.

Neural computation
We present a new algorithm to efficiently simulate random models of large neural networks satisfying the property of time asynchrony. The model parameters (average firing rate, number of neurons, synaptic connection probability, and postsynaptic dura...

Permitted Sets and Convex Coding in Nonthreshold Linear Networks.

Neural computation
Hebbian theory proposes that ensembles of neurons form a basis for neural processing. It is possible to gain insight into the activity patterns of these neural ensembles through a binary analysis, regarding neurons as either active or inactive. The f...

Edge detection in single multimode fiber imaging based on deep learning.

Optics express
We propose a new edge detection scheme based on deep learning in single multimode fiber imaging. In this scheme, we creatively design a novel neural network, whose input is a one-dimensional light intensity sequence, and the output is the edge detect...

Research on mobile traffic data augmentation methods based on SA-ACGAN-GN.

Mathematical biosciences and engineering : MBE
With the rapid development and application of the mobile Internet, it is necessary to analyze and classify mobile traffic to meet the needs of users. Due to the difficulty in collecting some application data, the mobile traffic data presents a long-t...

Relationship between the kernel size of a convolutional layer and the optical point spread function in ghost imaging using deep learning for identifying defect locations.

Applied optics
We explore the contribution of convolutional neural networks to correcting for the effect of the point spread function (PSF) of the optics when applying ghost imaging (GI) combined with deep learning to identify defect positions in materials. GI can ...