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43626 No.76420  

Stochastic Pattern Recognition Dramatically Outperforms Conventional Techniques

>A stochastic computer, designed to help an autonomous vehicle navigate, outperforms a conventional computer by three orders of magnitude


Что думаешь, анон?

>> No.76422  

Как оно работает, ОП?

>> No.76423  


>Stochastic Pattern Recognition Dramatically Outperforms Conventional Techniques
>Что думаешь, анон?

какая неожиданность! журналешлюхи уже совсем пизданулись.

>> No.76424  

Если я правильно понял статью, примерно как из анекдота про логарифмическую линейку. "Что-то около 30-и".
Мимо крокодил

>> No.76426  

Интересно, для каких классов задач эта штука пригодна.
Пример там какой-то искусственный.

>We verified the proposed patter-recognition technique to orient an autonomous vehicle in a

known environment. At each time step, the vehicle computes the distance to the nearest
walls (parameters n,s,e and w, in Fig. 8). These parameters are the inputs of seven MSCs
(one for each zone of the plane) configured with specifics mean and sigma values
(parameters η and N in Fig. 4). Once the vehicle recognizes the environment (the class
recognized is the zone where it is the vehicle), a predefined movement is selected with the
objective to reach zone A (see Fig. 8). In different experiments were the vehicle was placed
randomly in the plane, the time steps needed to reach zone A were computed. In all cases,
the vehicle was able to reach zone A with a nearly minimum trajectory. In Fig. 9 we
compare the time steps required to reach zone A (symbols) with the optimum number of
time steps (solid line). Results show that the itinerary followed by the vehicle is very close
to the optimum trajectory thus demonstrating that the stochastic system is able to recognize
the zones at each point of the path followed.

>> No.76539  

Да вы лентяи же! И оп - самый ленивый.

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