This week, my work fell into two categories: Artificial Neural Networks and labrelated projects.
Artificial Neural Networks
 I played around with radial basis functions and kmeans classification algorithms for a bit in order to develop an algorithm to pick out various features of seismic signals. However, I soon realized that kmeans is an extremely slow algorithm in practice, and that radial basis functions are thus difficult to implement since their centers are chosen by the kmeans algorithm in practice.
 Thus, I moved on to artificial neural networks. Specifically, I chose to implement a sigmoidal neural network, where the activation function of each neuron is f(u) = 1/ (1 + eu/T), T constant, which is nice because it's bounded in [0, 1]. Classification, then, is achieved by generating a final output vector from the output layer of the form [c1, c2, c3, ..., cN] where N is the number of classes, ci = 1 (ideally) if the input is of class i, and ck = 0 otherwise.
 First, I built a network with randomly generated weights, ten neurons in the one hidden layer, and two output neurons  to simply classify [1, 0] (earthquake) and [0, 1] (not an earthquake). I ran this on fake input I generated myself, and it quickly converged to error 0. Thus, I decided to built a network for real data.
 My current network is a 2layer, 10 neuron / 2 neuron sigmoidal network that also classified earthquake / not an earthquake. It trains in roughly 80  100 iterations (it's learning curve on training data it attached). It decimates full data from DataViewer by a factor of 256 in order to run faster.
 Next steps: currently, my greatest limitation is data  I can use US Geological Survey statistics to classify each earthquake (so that N = 10, rather than 2, for example), but I would like definite training data on people, cars, trucks, etc. for supervised learning, in order to develop those classes. Currently, however, the seismometers are being used for mine and Yaakov's triangulation project, so this may have to wait a few days.
LabRelated Projects
 I apologize for all of the Elogs, but I changed the filters in the RMS system (to elliptic and butterworth filters) and changed the seismic.strip display file.
 I repositioned the seismometers so that Yaakov and I can triangulate signals and determine seismic noise hotspots (as a sideproject).
Right now I'm going to try for more classes based on USGS statistics, and I will also explore other data sources Den suggested.
Thanks for your help, everybody in 40m!
