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#211
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Low carb diets
OmegaZero2003 wrote:
"Proton Soup" wrote... All engineers should know what superposition is. Are you trying to be condescending? Who? Me? Sorry. I was probably a little. It seemed elementary considering the responses seemed to be intelligent but missed major aspects of this. No they didn't. That was a representation in your own wetware. -- -Wayne |
#212
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Low carb diets
OmegaZero2003 wrote:
Did you bother to see the papers on computing and representation I referenced? Nope! 8-) See, I have a limited capacity for curiosity, and I suspect we're arguing about subtleties that verge on the meaningless. At the very least, a lot is being lost in translation. I do not care what the neurophsyiological response of a crayfish CNS is; there ain't any instruments yet that can tell just what processes and properties in *any* part of a NN exactly *represent* a "piece" of information - even given what the definition of "information" is (beyond a difference). The problem I have with this is that there's a point, with a very small number of neurons, where this distinction vanishes. This is the same problem most researchers have with the idea of "emergence". Beyond a high level of complexity, the network representation is probably closest to a high- dimensional hologram. At a low level of complexity, it's probably pretty much like an ANN. Is the distinction one of topological significance, or is it really all the same thing? In terms of computational neuroscience and ANNs(artificial neural net), remember that the ANN is a couple orders of magnitude less sophisticated (at least) (using simple I/O transforms and connection schemes used to build multi-layer ANNS) than the real thing in situ. I never claimed otherwise: I brought ANN's into the discussion because of the clear understanding of the roles of threshold and saturation on their behavior. -- -Wayne |
#213
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Low carb diets
OmegaZero2003 wrote: "Proton Soup" wrote in message ... On Sun, 21 Dec 2003 06:29:45 GMT, "OmegaZero2003" wrote: BTW, as a PS to my other answer post, here are some linear systems. - those characterizable by linear algebra. there are lots of these! - Hamiltonian oscillators and like systems. (the direction field specifically) - continuous-time systems like electrical networks, many mechanical systems Only simple RLC electrical networks fall into this category. And even then, it's just a theoretical assumption over the useful operating range. Too much current or voltage or flux will flux up your circuit. Linear electrical networks only exist on paper. My original point to the OP on the topic was a retort to the statement that *all* systems are nonlinear. That is not true. - any discrete system with a transfer function whose input, response and output functions depend on one variable - any systems preserving homogeneity (output proportional to input) and superposition (a way of combining linear functions such that the result is a linear function) Even non-deterministic systems can be modeled using statistics for linear dynamics. But the main point to not be belabored is that there are linear systems on nature and manmade (1) Most systems *are* non-linear but some of those are characterizable using linear methods to some degree of accuracy; you did make something like this point. (1) Schwarz, Ralph J. and Friedland, Bernard, 1965, Linear Systems, New York: McGraw-Hill Book Company, 521 pp. --- Proton Soup "If I drink water I will have to go to the bathroom and how can I use the bathroom when my people are in bondage?" -Saddam Hussein As several people have pointed out, linear vs. non--linear, per se, is meaningless. It all depends on the description. Some things are exactly linear (in the right description.) Sometimes linear is just local -- but even if local, this can provide quantitative information. (The example that comes to mind is the tumbling book. Two directions are stable, one is not. Linear analysis shows this.) -- Tom Morley | Same roads | Same rights | Same rules AIM: DocTDM |
#214
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Low carb diets
In article ,
Elzinator no one@com wrote: Lyle McDonald wrote: Ok, since the book project this was originally written for is unlikely to ever get done, I figured I'd post it. It's a long (11 pages) chapter/piece examining the pros/cons of the major dietary camps Dude, just upload it to your website! That's what it's for. I had snagged it, fixed typos and formatting, and put in in the archives at: http://www.trygve.com/mfwalylediet.html I haven't put in any links to it, but I can if that's okay. -- soc.singles FAQ [ Nyx Net, free ISP ] Misc.Fitness.Weights page www.trygve.com/ssfaq.html [ http://www.nyx.net ] www.trygve.com/mfw.html today's special featu Santa Claus, Fugitive From Justice on America's Most Wanton: http://www.trygve.com/mostwanton.html |
#215
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Low carb diets
"Tom Morley" wrote in message link.net... OmegaZero2003 wrote: "Proton Soup" wrote in message ... On Sun, 21 Dec 2003 06:29:45 GMT, "OmegaZero2003" wrote: BTW, as a PS to my other answer post, here are some linear systems. - those characterizable by linear algebra. there are lots of these! - Hamiltonian oscillators and like systems. (the direction field specifically) - continuous-time systems like electrical networks, many mechanical systems Only simple RLC electrical networks fall into this category. And even then, it's just a theoretical assumption over the useful operating range. Too much current or voltage or flux will flux up your circuit. Linear electrical networks only exist on paper. My original point to the OP on the topic was a retort to the statement that *all* systems are nonlinear. That is not true. - any discrete system with a transfer function whose input, response and output functions depend on one variable - any systems preserving homogeneity (output proportional to input) and superposition (a way of combining linear functions such that the result is a linear function) Even non-deterministic systems can be modeled using statistics for linear dynamics. But the main point to not be belabored is that there are linear systems on nature and manmade (1) Most systems *are* non-linear but some of those are characterizable using linear methods to some degree of accuracy; you did make something like this point. (1) Schwarz, Ralph J. and Friedland, Bernard, 1965, Linear Systems, New York: McGraw-Hill Book Company, 521 pp. --- Proton Soup "If I drink water I will have to go to the bathroom and how can I use the bathroom when my people are in bondage?" -Saddam Hussein As several people have pointed out, linear vs. non--linear, per se, is meaningless. It all depends on the description. Some things are exactly linear (in the right description.). Sometimes linear is just local -- but even if local, this can provide quantitative information. Sure - but that is known as a subclassed system. You are only examining it within a range of I/O/Xfer_function(s). Which is fine as far as it goes, I was referring to a system that exhibits true linear behavior throughout all known or extraploated ranges of input. (The example that comes to mind is the tumbling book. Two directions are stable, one is not. Linear analysis shows this.) Yes; although the point that was made , as I now understand, was about biological system, which certainly have more than the bulk of examples of non-lineear systems. -- Tom Morley | Same roads | Same rights | Same rules AIM: DocTDM |
#216
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Low carb diets
"Wayne S. Hill" wrote in message ... OmegaZero2003 wrote: "Proton Soup" wrote... All engineers should know what superposition is. Are you trying to be condescending? Who? Me? Sorry. I was probably a little. It seemed elementary considering the responses seemed to be intelligent but missed major aspects of this. No they didn't. That was a representation in your own wetware. How do you know I am not an ANN! You still have not shown how robustness is a function of saturation and/or thresholding. Although after thinking about it, in an oblique way, one can make up a story about it - a mind game ala Einstein. I.e., theoretically, I can imagine that a system can be thought of as robust if it escapes deterioration/degradation and/or elimination from the context/environment if it exhibits saturation/thresholding and that prevents state spaces leading to elimination. Coming up with a *real* example of such a charaterization in nature is left to the reader. -- -Wayne |
#217
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Low carb diets
"Wayne S. Hill" wrote in message ... OmegaZero2003 wrote: Did you bother to see the papers on computing and representation I referenced? Nope! 8-) See, I have a limited capacity for curiosity, and I suspect we're arguing about subtleties that verge on the meaningless. At the very least, a lot is being lost in translation. OK. I do not care what the neurophsyiological response of a crayfish CNS is; there ain't any instruments yet that can tell just what processes and properties in *any* part of a NN exactly *represent* a "piece" of information - even given what the definition of "information" is (beyond a difference). The problem I have with this is that there's a point, with a very small number of neurons, where this distinction vanishes. First, I suspect that that type of system is uninteresting. Second, it probably does not exist as a real system in situ' one can take away only so much of a system auntil it ceases *being* anything like what you were trying to show in the first place. Such is the case with a system whose function is representation (and transformation/translation/signalling). Third, that distinction is not a quatitative one - it is qualitative. take away the neurochemical soup for example, and what you show about information representation is apt to be misleading at best. *Analysis* (in the form of reductionism)is not always a good approach when dealing with complexity . This is the same problem most researchers have with the idea of "emergence". Beyond a high level of complexity, the network representation is probably closest to a high- But that is only the network representation; one of several maps, none of which is the territory. And most neuroscience researchers or AI researchers for that matter, so not have a problem with emergence. It is quite well described and accepted. Again, a really good book is Alwyn Scott's! I recommend it to any scientist I speak with (just as I recommend Wolfram's work, and Bucky Fuller's Synergetics). dimensional hologram. At a low level of complexity, it's probably pretty much like an ANN. Is the distinction one of topological significance, or is it really all the same thing? I don't follow; I don;t think even a highly-connected network like the brain has properties at the network level (nodes, connections, vertices etc.) that are appropriate in a discussion about holographical metaphors. Now, quantum effects, or other field effects -now we're talking. In terms of computational neuroscience and ANNs(artificial neural net), remember that the ANN is a couple orders of magnitude less sophisticated (at least) (using simple I/O transforms and connection schemes used to build multi-layer ANNS) than the real thing in situ. I never claimed otherwise: I brought ANN's into the discussion because of the clear understanding of the roles of threshold and saturation on their behavior. YEs - OK - I understand. But those are man-made systems that, llike I said above, are so abstracted, or rahter, simplified from the actual NN in the CNS -in situ with all the attendent functions provided by messenger molecules, densities , field effects etc., that the analysis has analysed away any chance of getting a parsimonious, satisfying sanswer to things like representation in a real brain. -- -Wayne |
#218
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Low carb diets
OmegaZero2003 wrote:
"Wayne S. Hill" wrote... The problem I have with this is that there's a point, with a very small number of neurons, where this distinction vanishes. First, I suspect that that type of system is uninteresting. Perhaps to you, but I've found that ANNs have unique properties for state space analysis. The chief one is this: given a set of inputs, each considered a different dimension for the state space of the problem, ANNs have the property of being able to scale each neighborhood of the state space differently. This is exceedingly difficult to achieve with explicit state space analysis techniques. -- -Wayne |
#219
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Low carb diets
"Wayne S. Hill" wrote in message ... OmegaZero2003 wrote: "Wayne S. Hill" wrote... The problem I have with this is that there's a point, with a very small number of neurons, where this distinction vanishes. First, I suspect that that type of system is uninteresting. Perhaps to you, but I've found that ANNs have unique properties for state space analysis. The chief one is this: given a set of inputs, each considered a different dimension for the state space of the problem, ANNs have the property of being able to scale each neighborhood of the state space differently. This is exceedingly difficult to achieve with explicit state space analysis techniques. Well - yeah - classifiers is a classic use for such. I meant from a research_into_brains standpoint, not man-made *A* NNs applied to other problems. -- -Wayne |
#220
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Low carb diets
In article ,
Lyle McDonald wrote: I can also report empirically the feedback I've gotten. This was from a few years ago (on the lowcarb-l list) from folks comparing things like Isocaloric (33/33/33) diets to Bodyopus (CKD) types of diets. These were motivated bodybuilder/athletic types who are known for being anal compulsive about their diet and who were using similar protein inakes and caloric deficits (and weight training and the rest). At *most*, the variance in fat loss/LBM loss was ~3 lbs over 12 weeks. That is, they might report 3 lbs more fat lost and 3 lbs more LBM maintained over that period. Adding: a. Even then, the effects weren't consistent. Some folks did better on CKD's, some folks better on Isocaloric (and lost more muscle on the CKD). Meaning there was no consistent pattern with one diet being absolutely superior. .. . . b. 3 lbs is within measurement error (sorry, this is the cynic in me speaking). Hell, it's within the error of glycogen and water balance. c. 3 lbs of fat vs LBM is hardly relevant for the majority of dieters. For an athlete or bodybuilder, yeah, it matters. But without a consistently superior diet or a way to know who will be ideally suited for one or the other, the above is kind of meaningless (at this point, there's no good way to apply it). A consistent difference of 3 lbs would be worthwhile. If the maximum difference measured is 3 lbs, and some measurements had the opposite sign, then I'd guess the average is unde 1 lb. That's well within the measurement error noise. Seth -- "There is no such thing as an essential carbohydrate" -- Will Brink Except sushi rice, seaweed, and wasabi. |
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