Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
Adaptive Filtering: Algorithms and Practical Implementation
Adaptive Filtering: Algorithms and Practical Implementation
Investigation of Adaptive Filtering for Noise Cancellation inECG signals
IMSCCS '07 Proceedings of the Second International Multi-Symposiums on Computer and Computational Sciences
The Applications and Simulation of Adaptive Filter in Noise Canceling
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 04
A survey: algorithms simulating bee swarm intelligence
Artificial Intelligence Review
Parameter Tuning for the Artificial Bee Colony Algorithm
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Computer Methods and Programs in Biomedicine
Entropy based Binary Particle Swarm Optimization and classification for ear detection
Engineering Applications of Artificial Intelligence
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Computerized processes are supportive in the new age of medical treatment. Biomedical signals which are collected from the human body supply or important useful data that are related with the biological actions of human body organs. However, these signals may also contain some noise. Heart waves are commonly classified as biomedical signals and are non-stationary due to their statistical specifications. The probability distributions of the noise are very different, and for this reason there is no common method to remove the noise. In this study, adaptive filters are used for noise elimination and the transcranial Doppler signal is analyzed. The artificial bee colony algorithm was employed to design the adaptive IIR filters for noise elimination on the transcranial Doppler signal and the results were compared to those obtained by the methods based on popular and recently introduced evolutionary algorithms and conventional methods.