AIMC Topic: Neural Networks, Computer

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A renaissance of neural networks in drug discovery.

Expert opinion on drug discovery
INTRODUCTION: Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to choose the mo...

Discrimination of systolic and diastolic dysfunctions using multi-layer perceptron in heart rate variability analysis.

Computers in biology and medicine
In this study, the heart rate variability (HRV) analysis is used to distinguish patients with systolic congestive heart failure (CHF) from patients with diastolic CHF. In the analysis performed, the best accuracy performances of short-term HRV measur...

On the development of conjunctival hyperemia computer-assisted diagnosis tools: Influence of feature selection and class imbalance in automatic gradings.

Artificial intelligence in medicine
OBJECTIVE: The sudden increase of blood flow in the bulbar conjunctiva, known as hyperemia, is associated to a red hue of variable intensity. Experts measure hyperemia using levels in a grading scale, a procedure that is subjective, non-repeatable an...

Linear readout of object manifolds.

Physical review. E
Objects are represented in sensory systems by continuous manifolds due to sensitivity of neuronal responses to changes in physical features such as location, orientation, and intensity. What makes certain sensory representations better suited for inv...

Diagnosis of Diabetes Mellitus by Extraction of Morphological Features of Red Blood Cells Using an Artificial Neural Network.

Experimental and clinical endocrinology & diabetes : official journal, German Society of Endocrinology [and] German Diabetes Association
Diabetes mellitus is a metabolic disorder characterized by varying hyperglycemias either due to insufficient secretion of insulin by the pancreas or improper utilization of glucose. The study was aimed to investigate the association of morphological...

Quadrupedal Robot Locomotion: A Biologically Inspired Approach and Its Hardware Implementation.

Computational intelligence and neuroscience
A bioinspired locomotion system for a quadruped robot is presented. Locomotion is achieved by a spiking neural network (SNN) that acts as a Central Pattern Generator (CPG) producing different locomotion patterns represented by their raster plots. To ...

On Stabilization of Quantized Sampled-Data Neural-Network-Based Control Systems.

IEEE transactions on cybernetics
This paper investigates the problem of stabilization of sampled-data neural-network-based systems with state quantization. Different with previous works, the communication limitation of state quantization is considered for the first time. More specif...

Growing Homophilic Networks Are Natural Navigable Small Worlds.

PloS one
Navigability, an ability to find a logarithmically short path between elements using only local information, is one of the most fascinating properties of real-life networks. However, the exact mechanism responsible for the formation of navigation pro...

An Ensemble Approach for Cognitive Fault Detection and Isolation in Sensor Networks.

International journal of neural systems
Cognitive fault detection and diagnosis systems are systems able to provide timely information about possibly occurring faults without requiring any a priori knowledge about the process generating the data or the possible faults. This ability is cruc...

Methodology of Recurrent Laguerre-Volterra Network for Modeling Nonlinear Dynamic Systems.

IEEE transactions on neural networks and learning systems
In this paper, we have introduced a general modeling approach for dynamic nonlinear systems that utilizes a variant of the simulated annealing algorithm for training the Laguerre-Volterra network (LVN) to overcome the local minima and convergence pro...