AIMC Topic: Neural Networks, Computer

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Constrained chaos in three-module neural network enables to execute multiple tasks simultaneously.

Neuroscience research
Constrained chaos introduced into a three-module neural network having feedforward inter-module structure could have potential abilities to execute multiple tasks simultaneously. Each module consists of a large number of binary state (±1) neurons. Th...

A fusion framework to extract typical treatment patterns from electronic medical records.

Artificial intelligence in medicine
OBJECTIVE: Electronic Medical Records (EMRs) contain temporal and heterogeneous doctor order information that can be used for treatment pattern discovery. Our objective is to identify "right patient", "right drug", "right dose", "right route", and "r...

Prediction and optimization of slaughter weight in meat-type quails using artificial neural network modeling.

Poultry science
Carcass yield of meat-type quails is strongly correlated with the weight of the birds at slaughter (slaughter weight [SW]; body weight at 45 D of age). Moreover, prediction of superior animals for SW at the earlier stages of the rearing period is fav...

Global synchronization of coupled delayed memristive reaction-diffusion neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper focuses on the global exponential synchronization of multiple memristive reaction-diffusion neural networks (MRDNNs) with time delay. Due to introducing the influences of space as well as time on state variables and replacing resistors wit...

A novel compound wind speed forecasting model based on the back propagation neural network optimized by bat algorithm.

Environmental science and pollution research international
Wind power, a clean and renewable resource, is regarded as one of the most promising and economical resources during the transformation from fossil fuels to new energy resources. Thus, the accuracy of wind speed forecasting work is very important to ...

A CNN-Assisted Enhanced Audio Signal Processing for Speech Emotion Recognition.

Sensors (Basel, Switzerland)
Speech is the most significant mode of communication among human beings and a potential method for human-computer interaction (HCI) by using a microphone sensor. Quantifiable emotion recognition using these sensors from speech signals is an emerging ...

Automatic detection of blood content in capsule endoscopy images based on a deep convolutional neural network.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Detecting blood content in the gastrointestinal tract is one of the crucial applications of capsule endoscopy (CE). The suspected blood indicator (SBI) is a conventional tool used to automatically tag images depicting possible ble...

Dual-functional neural network for bilateral hippocampi segmentation and diagnosis of Alzheimer's disease.

International journal of computer assisted radiology and surgery
PURPOSE: Knowing the course of Alzheimer's disease is very important to prevent the deterioration of the disease, and accurate segmentation of sensitive lesions can provide a visual basis for the diagnosis results. This study proposes an improved end...

Sparse Ensemble Machine Learning to Improve Robustness of Long-Term Decoding in iBMIs.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper presents a novel sparse ensemble based machine learning approach to enhance robustness of intracortical Brain Machine Interfaces (iBMIs) in the face of non-stationary distribution of input neural data across time. Each classifier in the en...