AIMC Topic: Neural Networks, Computer

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Quality changes and predictive models of radial basis function neural networks for brined common carp (Cyprinus carpio) fillets during frozen storage.

Food chemistry
To investigate and predict quality of 2% brined common carp (Cyprinus carpio) fillets during frozen storage, free fatty acids (FFA), salt extractable protein (SEP), total sulfhydryl (SH) content, and Ca(2+)-ATPase activity were determined at 261 K, 2...

Analysis of global O(t(-α)) stability and global asymptotical periodicity for a class of fractional-order complex-valued neural networks with time varying delays.

Neural networks : the official journal of the International Neural Network Society
In this paper, the problem of the global O(t(-α)) stability and global asymptotic periodicity for a class of fractional-order complex-valued neural networks (FCVNNs) with time varying delays is investigated. By constructing suitable Lyapunov function...

Finite-time robust stabilization of uncertain delayed neural networks with discontinuous activations via delayed feedback control.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the finite-time robust stabilization of delayed neural networks (DNNs) in the presence of discontinuous activations and parameter uncertainties. By using the nonsmooth analysis and control theory, a delayed controller is ...

Projective synchronization of nonidentical fractional-order neural networks based on sliding mode controller.

Neural networks : the official journal of the International Neural Network Society
This paper investigates global projective synchronization of nonidentical fractional-order neural networks (FNNs) based on sliding mode control technique. We firstly construct a fractional-order integral sliding surface. Then, according to the slidin...

Predicting concrete corrosion of sewers using artificial neural network.

Water research
Corrosion is often a major failure mechanism for concrete sewers and under such circumstances the sewer service life is largely determined by the progression of microbially induced concrete corrosion. The modelling of sewer processes has become possi...

Prototype-based models in machine learning.

Wiley interdisciplinary reviews. Cognitive science
An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the contex...

Multiple Linear Regression and Artificial Neural Network to Predict Blood Glucose in Overweight Patients.

Experimental and clinical endocrinology & diabetes : official journal, German Society of Endocrinology [and] German Diabetes Association
BACKGROUND: Overweight individuals are at higher risk for developing type II diabetes than the general population. We conducted this study to analyze the correlation between blood glucose and biochemical parameters, and developed a blood glucose pred...

Accurate Segmentation of CT Male Pelvic Organs via Regression-Based Deformable Models and Multi-Task Random Forests.

IEEE transactions on medical imaging
Segmenting male pelvic organs from CT images is a prerequisite for prostate cancer radiotherapy. The efficacy of radiation treatment highly depends on segmentation accuracy. However, accurate segmentation of male pelvic organs is challenging due to l...

Advanced Residuals Analysis for Determining the Number of PARAFAC Components in Dissolved Organic Matter.

Applied spectroscopy
Parallel factor analysis (PARAFAC) has facilitated an explosion in research connecting the fluorescence properties of dissolved organic matter (DOM) to its functions and biogeochemical cycling in natural and engineered systems. However, the validatio...

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sens...