Training Neural Networks with Genetic Algorithms

In this blog post I present my findings of an independent analytical and computational study of using genetic algorithms to train neural networks. This was my final project for an Introduction to Cognitive Science course that I took at The University of Texas at Austin, under Dr. David Beaver. My motivation comes from the fact …

Continue reading Training Neural Networks with Genetic Algorithms

Thoughts from a drunken party

Are there any utilitarian side-effects to a conscious attempt towards the dissolution of the self? It might seem an odd question to ask, for the very task of this self-learned dissolution is only taken up by those who have reached a state of mind that has conclusively disengaged from any utilitarian goals. I suppose I …

Continue reading Thoughts from a drunken party

Lyapunov Exponent of Logistic Map

Calculating the Lyapunov Exponent of a Time Series (with python code)

(In a later post I discuss a cleaner way to calculate the Lyapunov exponent for maps and particularly the logistic map, along with Mathematica code.) I found this method during my Masters while recreating the results of an interesting paper on how some standard tests for chaos fail to distinguish chaos from stochasticity (Stochastic neural network …

Continue reading Calculating the Lyapunov Exponent of a Time Series (with python code)