# Computing

## Ross: The Industries of the Future

The importance of a book like “The industries of the future”1 by Alec Ross can hardly be overstated.  By his own admission, “This book explores the industries that will drive the next 20 years of change to our economies and societies”… Read More ›

## Video Transcoding: Handbrake + libdvdcss

Suppose you had your collection of DVDs which you lawfully bought in the marketplace. Suppose you wanted to see them when you are running in the gym, on your iPad. You need to transcode them, i. e. make the conversion… Read More ›

## Feed-forward networks and teleology

Bertrand Russell, in “History of Western Philosophy” pgg. 86-87, writes: The atomists, unlike Socrates, Plato, and Aristotle, sought to explain the world without introducing the notion of purpose or final cause. The “final cause” of an occurrence is an event… Read More ›

## Market completion with Wishart variance

The following page documents the simulation happening in the model described here, i.e. the Wishart based stochastic volatility. The parameters for the Euler-Maruyama simulation are: 1. 1. 0.01. 2 4.8   Example of Arbitrage free volatility surface (dynamics of vol surface)… Read More ›

## Octave meshgrid, surf and video slideshow

Since the release of the splendid GUI, Octave has become again one of my favorite tools. Here is a simple and hopefully useful application. The following code is quite self-explanatory: tx = ty = linspace (-4, 4, 41)’; [xx, yy] = meshgrid… Read More ›

## Ipython: simple finite differences

Ipython as a prototyping tool for scientific computation is very neat and useful indeed. After the Win 8 minimal installation reviewed in a previous post, now we are going for some simple Crank Nicolson of a parabolic PDE. We are… Read More ›

## Ipython in Windows 8: “Hello World”

This post documents the installation of Ipython in Windows 8. As an example of Don Knuth’s Literate Programming, Ipython is simply great. One can devise the mathematical equations of a model, code the numerics and run the program against data.The… Read More ›

## Science Friction (1)

Mersenne numbers, when they are primes, are routinely used to feed MonteCarlo random number generation. They have the form: . Since not all of them are prime, we can use prime factorization of a sequence of big Mersenne numbers to… Read More ›

## Make video of (Markovian) density transition

Suppose one has managed to numerically compute the forward transition density of 2-dimensional Markov process under some finite difference algorithm (or finite elements). Of course at each time slice, there is going to be a surface of data. How about… Read More ›

## Theodicy 2.0

If someone is, like me, working all the time with RNGs and strives to produce MonteCarlo scenarios about events via computer simulations, he cannot help but thinking that different outcomes are due to different randomness structures (Sobol anyone?) In view… Read More ›