AIMC Topic: Neural Networks, Computer

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A Deep Learning Scheme for Motor Imagery Classification based on Restricted Boltzmann Machines.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Motor imagery classification is an important topic in brain-computer interface (BCI) research that enables the recognition of a subject's intension to, e.g., implement prosthesis control. The brain dynamics of motor imagery are usually measured by el...

Optogenetics in Silicon: A Neural Processor for Predicting Optically Active Neural Networks.

IEEE transactions on biomedical circuits and systems
We present a reconfigurable neural processor for real-time simulation and prediction of opto-neural behaviour. We combined a detailed Hodgkin-Huxley CA3 neuron integrated with a four-state Channelrhodopsin-2 (ChR2) model into reconfigurable silicon h...

Synchronization of Markovian jumping inertial neural networks and its applications in image encryption.

Neural networks : the official journal of the International Neural Network Society
This study is mainly concerned with the problem on synchronization criteria for Markovian jumping time delayed bidirectional associative memory neural networks and their applications in secure image communications. Based on the variable transformatio...

A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242).

Computational intelligence and neuroscience
This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kine...

Deep Convolutional Extreme Learning Machine and Its Application in Handwritten Digit Classification.

Computational intelligence and neuroscience
In recent years, some deep learning methods have been developed and applied to image classification applications, such as convolutional neuron network (CNN) and deep belief network (DBN). However they are suffering from some problems like local minim...

Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

PloS one
One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transfe...

Cascade of multi-scale convolutional neural networks for bone suppression of chest radiographs in gradient domain.

Medical image analysis
Suppression of bony structures in chest radiographs (CXRs) is potentially useful for radiologists and computer-aided diagnostic schemes. In this paper, we present an effective deep learning method for bone suppression in single conventional CXR using...

Computational analysis of memory capacity in echo state networks.

Neural networks : the official journal of the International Neural Network Society
Reservoir computing became very popular due to its potential for efficient design of recurrent neural networks, exploiting the computational properties of the reservoir structure. Various approaches, ranging from appropriate reservoir initialization ...

Recurrent neural network based hybrid model for reconstructing gene regulatory network.

Computational biology and chemistry
One of the exciting problems in systems biology research is to decipher how genome controls the development of complex biological system. The gene regulatory networks (GRNs) help in the identification of regulatory interactions between genes and offe...