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I don't understand the argument here. Obviously you need some sort of amplification process to avoid noise. But there are amplifying processes that don't foll
by panic 8y ago
I don't understand the argument here. Obviously you need some sort of amplification process to avoid noise. But there are amplifying processes that don't follow the "discrete" Shannon model. Like, I'm pretty sure neurons themselves are an example -- they maintain a stable voltage (even with noise) until they depolarize and spike. The process of depolarization is fundamentally analog, integrating together all the synaptic inputs (and anything else that affects the voltage in the cell). It can't be modeled using a sequence of discrete symbols, but it's also stable over time in the presence of noise.
- Maybestring 8y ago>It can't be modeled using a sequence of discrete symbols, but it's also stable over time in the presence of noise. Did you mean can be? When you learned to be integrate continuous functions, I'm certain you learned to do it while scratching sequences of discrete symbols onto paper.
- panic 8y agoUsing discrete symbols to describe a continuous model is different than using a discrete model. In this case, the paper is arguing that a particular discrete model based on sequences of discrete symbols (Shannon information theory) applies to the problem, not an arbitrary model including things like integrals.