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- W4280492546 abstract "This chapter discusses the use of chaotic descriptors, such as dimension correlation, Lyapunov exponent and Hurst exponent, to train support vector machines. The World Health Organization, WHO, describes epilepsy as a chronic brain disease characterized by recurring seizures that affects people worldwide. Seizures are brief episodes of muscle contractions that could affect some part of the body or all of it, which sometimes are accompanied by loss of consciousness and control of bowel or bladder functions. Pattern recognition on electroencephalogram signals is a complex process that consumes an enormous amount of analysis time, even for professionals in the area. The extraction of certain features requires a previous processing involving the reconstruction of the dynamics of the system in the state space from a time series. Lyapunov exponents are the divergence rates of two close trajectories within an attractor with respect to time." @default.
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- W4280492546 date "2022-05-14" @default.
- W4280492546 modified "2023-10-18" @default.
- W4280492546 title "APSoC-Based Implementation of an EEG Classifier using Chaotic Descriptors" @default.
- W4280492546 doi "https://doi.org/10.1201/9781003145240-7" @default.
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