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fredreload
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Is the analog output a voltage, current, or a signal? I'm kind of confused.
fredreload said:Is the analog output a voltage, current, or a signal? I'm kind of confused.
Analog output of what?fredreload said:Is the analog output a voltage, current, or a signal? I'm kind of confused.
fredreload said:Is the analog output a voltage, current, or a signal? I'm kind of confused.
anorlunda said:Now you have several answers from people who have interpreted your question different ways. I invite you to try again. Better quality questions produce better answers.
He is a legend!Averagesupernova said:Or as one of my favorite wise posters on PF says: A question well stated is half answered.
fredreload said:I do believe that analyzing circuit plays an important role in determining consciousness. We all know that computer seems to "think", in its way with the CPU, and CPU is made up of complicated logic gates that comprises the integrated circuit. Now if we take such a circuit's functional behavior to the next level and allow parallel processing it just might become a real thinking unit. Consciousness might be something that arises from the circuit's functional behavior based on my speculation, but since anorlunda mentioned consciousness does not arise from circuit analysis, maybe you have something else in mind?
fredreload said:Computer only have 2 states, 0 and 1, but brain can have more states then that.
from http://web.williams.edu/Mathematics/sjmiller/public_html/105Sp10/addcomments/Hayes_ThirdBase.htm
Among all possible ways of writing the numbers up to a million, neither base 1,000,000 nor base 1 seems ideal; as a matter of fact, you could hardly do worse than either of these choices. Minimizing the number of digits causes an explosion in the alphabet of symbols, and vice versa; when you squish down one factor, the other squirts out. Evidently we need to optimize some joint measure of a number's width (how many digits it has) and its depth (how many different symbols can occupy each digit position). An obvious strategy is to minimize the product of these two quantities. In other words, if r is the radix and w is the width in digits, we want to minimize rw while holding rw constant.
Curiously, this problem is easier to solve if r and w are treated as continuous rather than integer variables—that is, if we allow a fractional base and a fractional number of digits. Then it turns out (see Figure 1) that the optimum radix is e, the base of the natural logarithms, with a numerical value of about 2.718. Because 3 is the integer closest to e, it is almost always the most economical integer radix (see Figure 2).
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As it happens, the first working ternary computer was built on the other side of the Iron Curtain. The machine was designed by Nikolai P. Brusentsov and his colleagues at Moscow State University and was named Setun, for a river that flows near the university campus. Some 50 machines were built between 1958 and 1965.
As if?jim hardy said:Would you pardon an old guy's ramble ?
Logarithms come to mind.jim hardy said:Who said the base has to be integer?
Absolutely. Even associating the electronic technology in a processor with the way a computer algorithm runs is pretty fruitless. The same algorithm can run with virtually any type of processor.meBigGuy said:Trying to in any way transition from circuit characteristics to consciousness is an exercise in futility.
anorlunda said:It is true that software runs on computer circuits, but the same software can run on many different kinds of computers. That leads one to say that the software's property does not arise from the particular circuits.
fredreload said:Actually that's a good point, we wouldn't know if there is a software running in our mind. We'll need some computer expert here.
No, digital computers and animal nervous systems are made up of different components. While digital computers use electronic circuits and software to process information, animal nervous systems use neurons and chemical signals to transmit information.
Yes, digital computers can perform many tasks that animal nervous systems can, such as processing information, making decisions, and controlling movements. However, they do so in a very different way and may not have the same level of complexity and adaptability as animal nervous systems.
No, digital computers and animal nervous systems have different levels of efficiency. Digital computers are very fast at processing information and can perform tasks accurately and consistently. Animal nervous systems, on the other hand, may not be as fast but have the ability to process information in a more parallel and adaptive way.
Yes, digital computers can be programmed to learn and adapt through machine learning algorithms. However, they may not have the same level of flexibility and adaptability as animal nervous systems, which can constantly learn and adapt to new situations without explicit programming.
No, digital computers and animal nervous systems have different levels of complexity. Digital computers can perform complex calculations and tasks very quickly, but they are limited by the instructions given to them. Animal nervous systems, on the other hand, have a high level of complexity due to the vast network of neurons and their ability to process information in parallel.