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Results of work in errors of transmission
Benoît Mandelbrot Mathematician
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There was an event there that was also a high point of my life. I was invited by Bell Labs to give a talk. I found upon arrival that very few people were there, but Pierce who was director of communications and several other people were there, together with their man who was had these models, and they asked me to present my work, which I did. This man at Bell who had had this hierarchy of levels of noisiness spoke up saying that you don't need all this fancy stuff, infinite means, infinite variances. "It's all very bad. I can do it with just hierarchy." And Pierce turned to him, and said with total scorn, "Yes, I know very well that you can represent the motion of the sun and planets around the earth by cycles, epicycles and so on. He represents it by ellipses. He may be right," or "He is probably right," or "It is worth listening to," I forgot the exact words. But Pierce understood my point. Need I say that this made a revolution in communications? Yes and no. Yes, to the extent that the reason why these errors were obtained is that because of not knowing what to do, everybody was transmitting at a very high signal to noise ratio for very few errors. The errors are very few; therefore any error collecting system was on only say one thousandth of the time. If it was on it was overwhelmed, therefore error correction was impossible, therefore it became clear to Bell, to IBM and to everybody that this was very bad engineering, not on the basis of details but of a very bad tree to climb on. You should transmit at a very much lower signal to noise ratio, have many errors, and pay lots to correct them. So, this actually put the wolf away from my door for a long time, because everybody was aware of the fact that by having an understandable, clean, few parameters, short model, I allowed people to abandon a very bad technology in favour of a better one, which I did not develop, of course.

Benoît Mandelbrot (1924-2010) discovered his ability to think about mathematics in images while working with the French Resistance during the Second World War, and is famous for his work on fractal geometry - the maths of the shapes found in nature.

Listeners: Daniel Zajdenweber Bernard Sapoval

Daniel Zajdenweber is a Professor at the College of Economics, University of Paris.

Bernard Sapoval is Research Director at C.N.R.S. Since 1983 his work has focused on the physics of fractals and irregular systems and structures and properties in general. The main themes are the fractal structure of diffusion fronts, the concept of percolation in a gradient, random walks in a probability gradient as a method to calculate the threshold of percolation in two dimensions, the concept of intercalation and invasion noise, observed, for example, in the absorbance of a liquid in a porous substance, prediction of the fractal dimension of certain corrosion figures, the possibility of increasing sharpness in fuzzy images by a numerical analysis using the concept of percolation in a gradient, calculation of the way a fractal model will respond to external stimulus and the correspondence between the electrochemical response of an irregular electrode and the absorbance of a membrane of the same geometry.

Duration: 2 minutes, 15 seconds

Date story recorded: May 1998

Date story went live: 24 January 2008