Title: Fractal Mechanisms in Neural Control Post by: claude on January 11, 2017, 07:19:40 PM http://www.physionet.org/tutorials/fmnc/index.shtml
Quote Fractal Mechanisms in Neural Control Human Heartbeat and Gait Dynamics in Health and Disease Introduction Fractal Analysis Methods Fractal Objects and Self-Similar Processes Mapping Real-World Time Series to Self-Similar Processes Detrended Fluctuation Analysis (DFA) Relationship Between Self-Similarity and Auto-Correlation Functions Fractal Dynamics of Human Heartbeat Is the Healthy Human Heartbeat Fractal? Does Fractal Scaling Break Down in Disease and Aging? Clinical Utility of Fractal Heart Rate Analysis Fractal Dynamics of Human Walking Is Healthy Gait Rhythm Fractal? Stability of Healthy Fractal Rhythm: Effects of Walking Rate Mechanisms of Fractal Gait Alterations of Fractal Dynamics with Aging and Disease Fractal Dynamics of Heart Rate and Gait: Implications and General Conclusions References Title: Re: Fractal Mechanisms in Neural Control Post by: Chillheimer on January 11, 2017, 09:42:35 PM Also: balance when standing shows fractal patterns (https://www.fractal.institute/balance/).
Title: Re: Fractal Mechanisms in Neural Control Post by: claude on January 11, 2017, 10:23:10 PM I had hoped to use the detrended fluctuation analysis in place of correlation exponent calculations for analysing iterated function system fractal dimension, but it failed miserably (ended up with near 0.5 no matter the transforms which is the same as the white noise that controls the chaos game). Is a pity, because DFA is O(n log n), much faster than CE's O(n^2). I attached my implementation with some coloured noise sources as input, here's the output: Code: white 0.490273 |