Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
Artificial Intelligence Review
The Practical Handbook of Genetic Algorithms: Applications, Second Edition
The Practical Handbook of Genetic Algorithms: Applications, Second Edition
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Fitting Optimal Piecewise Linear Functions Using Genetic Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Online Algorithm for Segmenting Time Series
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Signal compression by piecewise linear non-interpolating approximation
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03
QoS-based cooperative algorithm for integral multi-commodity flow problem
Computer Communications
Artificial Intelligence in Medicine
Data structure-guided development of electrocardiographic signal characterization and classification
Artificial Intelligence in Medicine
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Functional piecewise approximation seeks data representation that is compact, highly simplified and meaningful. This study presents a genetic algorithm (GA)-based approach for computing a piecewise polynomial representation of functions, with the focus being on piecewise linear approximation in an application of biomedical spectral data. The area of piecewise linear approximation has been researched in the past four decades approximately, and the method presented here is compared with another well-known approach. The expansion of this method to piecewise polynomial representation is shown to be straightforward. Finally, the application of this method as a feature extraction method for classification of a dataset of feature vectors, specifically biomedical spectra, is demonstrated.