@inproceedings{scholars9096, pages = {310--314}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, journal = {Proceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017}, title = {Evaluation of simulated VEP signals on basis of Higuchi and Katz's algorithm}, year = {2017}, doi = {10.1109/ICSIPA.2017.8120627}, note = {cited By 2; Conference of 5th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017 ; Conference Date: 12 September 2017 Through 14 September 2017; Conference Code:132915}, keywords = {Biomedical signal processing; Cosine transforms; Electroencephalography; Finite difference method; Fractals; Image processing; Parameter estimation, Colored noise; Cosine functions; Higuchi; Higuchi's algorithms; Katz; Linearly proportional; Noise power; Visual evoked potential, Fractal dimension}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041388437&doi=10.1109\%2fICSIPA.2017.8120627&partnerID=40&md5=0956f96b2e3e4635b7df93b1ad433ed4}, abstract = {This paper investigates the influences of noise power and signals length towards the fractal dimension (FD) of a short and non-complex visual evoked potential (VEP). Higuchi and Katz's algorithms have been used to estimate the fractal dimension of the simulated VEPs with the various parameter. To examine the performance of both algorithms, the parameter of colored noise and window length of the signal were varied. Weierstrass cosine function was generated with a known FD for validation. Katz's FD of the VEPs are linearly proportional to the noise power, as it measures the roughness of the signal. Higuchi's algorithm is highly affected by noise. The FD decreases as noise power increased until it reaches the plateau when the noise power equals to 0.05. It was found that Katz's FD has no significant effect of window length, meanwhile, Higuchi's FD increases as window length increases. {\^A}{\copyright} 2017 IEEE.}, author = {Radzi, S. S. M. and Asirvadam, V. S. and Dass, S. C. and Hutapea, D. K. Y.}, isbn = {9781509055593} }