Monthly Archives: December 2013

Neural networks and image recognition

I’ve been enjoying xmas holidays doing some machine learning and Neural Network programming, in the general context of ‘Target Recognition’, more specifically, trying to teach my computer how to decide whether a person in an image is male or female. This … Continue reading

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Fourier Transformation for dummies

Absolutely brilliant layman explanation of Fourier Transform – even I could understand it…! 😉 http://forums.parallax.com/attachment.php?attachmentid=75800&d=1291048674

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Excellent intro to DSP by Steven W. Smith

Just found this absolutely brilliant intro to Digital Signal Processing (and a lot of other useful stuff) by Steven W. Smith.

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Architecture and Agility: Married, Divorced, or Just Good Friends?

Architecture and Agility: Married, Divorced, or Just Good Friends?.

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Surrounded by average people… what’s the likely IQ of your neighbour…?

IQ, the intelligence quotient, is defined as a normal distribution with mean of 100, and a standard deviation of 15. According to James Flynn, people with IQ 70 or less, are mentally retarded, while those with IQ 130 or more, … Continue reading

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A tribute to Swedish innovation and entrepreneurship

Gripen – a state of the art 4G fighter developed in a country of 9 million

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Robotics

Cooperation among robots

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Probability Distributions for Dummies – Drunken walks and blindfolded archers

After having spent a few evenings exploring Python’s various math & science modules, specifically those dealing with probability, simulation and statistics, perhaps it’s time for a brief summary. In my previous recent posts, I’ve gone thru concepts such as mild … Continue reading

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How accurate and precise is your aim ? Skilled and unskilled archers

In a previous post, The Blindfolded Archer, I described the difference between wild and mild randomness, the former exemplified by the blindfolded archer and the Cauchy probability distribution, and characterised by the “long tail”, that is, precence of extreme events, … Continue reading

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Ever been really really drunk…? Made a fool of yourself..? Here’s a strategy for U if you need to run…

Continuing my experiments with Python’s various mathematical, statistical and scientific libraries, I decided to do a simulation of the Drunkard’s Walk, using different probability distributions. Unless you’ve ever been in that totally intoxicated situation where your vision is blurred, your … Continue reading

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