Neural networks and the bias/variance dilemma
Neural Computation
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy lattice neurocomputing (FLN) models
Neural Networks
Automatic identification of sound source position employing neural networks and rough sets
Pattern Recognition Letters - Special issue: Rough sets, pattern recognition and data mining
The Journal of Machine Learning Research
EEG signal classification using wavelet feature extraction and a mixture of expert model
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Intelligent target recognition based on wavelet packet neural network
Expert Systems with Applications: An International Journal
Recurrent neural networks employing Lyapunov exponents for EEG signals classification
Expert Systems with Applications: An International Journal
An investigation of neuro-fuzzy systems in psychosomatic disorders
Expert Systems with Applications: An International Journal
A multilayer perceptron-based medical decision support system for heart disease diagnosis
Expert Systems with Applications: An International Journal
Transform coding of audio signals using perceptual noise criteria
IEEE Journal on Selected Areas in Communications
EURASIP Journal on Advances in Signal Processing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Computer Methods and Programs in Biomedicine
Rule extraction from DEWNN to solve classification and regression problems
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Hi-index | 12.05 |
This work focuses on the implementation of an autonomous system appropriate for long-term, unsupervised monitoring of bowel sounds, captured by means of abdominal surface vibrations. The autonomous intestinal motility analysis system (AIMAS) promises to deliver new potentials in gastrointestinal auscultation, towards the establishment of novel non-invasive methods for prolonged intestinal monitoring and diagnosis over functional disorders. The system was developed utilizing time-frequency features and wavelet-adapted parameters in combination with multi-layer perceptrons, that exhibit remarkable adaptation in pattern classification applications. Various network topologies and sizes were tested in combination with different features' sets. Quantitative analysis and validation results showed that the implemented system exhibits an overall recognition accuracy of 94.84%, while the error in separating bowel sounds from other sound patterns, representing interfering noises, was 2.19%.