A while ago Bryon produced some equations. Among them:
Just a nit pick here: operator precedence being what it is, the equation as written would be evaluated as CA = (1/L) + N + D. But your intent to have all component accuracy be inversely proportional to all three of loss, noise, and distortion would be better written as CA = 1/(L+N+D).
I've been wrestling with this one because I don't think of a component's resolution as limited by the resolution of the source -- that is, the output at any given moment may be limited by the source, but that is not be the component's inherent resolution limit. It is only when the source resolution exceeds the component resolution that you can know anything about the component resolution, at which point the source resolution ceases to be a factor. Or maybe I'm missing your point.
I have a couple of thoughts on these "sum of" relationships. 1) Some types of errors may not be simply propagated through downstream components, but may actually be reinforced by them. This kind of error may result in an exponential relationship, rather than a simple additive one. This would be an example of bad synergy among components. 2) In some cases, the entire chain may be limited by a single component. Resolution, for instance, may well be a function of the least resolving component in the chain, rather than the sum of small losses in several components. Neutrality, on the other hand, is likely the sum of the components contribution.
I realize that you did not intend these to be strict mathematical relationships, but these are some ideas that occurred to me about other types of relationships among components.
1. CA = (1/L+N+D). A COMPONENT’S ACCURACY is determined by the amount of loss, noise, and distortion within the component. More specifically, a component's accuracy is INVERSELY PROPORTIONAL to its loss, noise, and distortion.
Just a nit pick here: operator precedence being what it is, the equation as written would be evaluated as CA = (1/L) + N + D. But your intent to have all component accuracy be inversely proportional to all three of loss, noise, and distortion would be better written as CA = 1/(L+N+D).
3. CR = CA + FR. A COMPONENT’S RESOLUTION is determined by the accuracy of the component and the format resolution of the source. Specifically, a component's resolution is DIRECTLY PROPORTIONAL to its accuracy and the format resolution.
I've been wrestling with this one because I don't think of a component's resolution as limited by the resolution of the source -- that is, the output at any given moment may be limited by the source, but that is not be the component's inherent resolution limit. It is only when the source resolution exceeds the component resolution that you can know anything about the component resolution, at which point the source resolution ceases to be a factor. Or maybe I'm missing your point.
4. SA = SoCA. A SYSTEM’S ACCURACY is determined by the sum of its components’ accuracy. Specifically, they are DIRECTLY PROPORTIONAL.
5. SN = SoCN. A SYSTEM’S NEUTRALITY is determined by the sum of its components’ neutrality. Specifically, they are DIRECTLY PROPORTIONAL.
I have a couple of thoughts on these "sum of" relationships. 1) Some types of errors may not be simply propagated through downstream components, but may actually be reinforced by them. This kind of error may result in an exponential relationship, rather than a simple additive one. This would be an example of bad synergy among components. 2) In some cases, the entire chain may be limited by a single component. Resolution, for instance, may well be a function of the least resolving component in the chain, rather than the sum of small losses in several components. Neutrality, on the other hand, is likely the sum of the components contribution.
I realize that you did not intend these to be strict mathematical relationships, but these are some ideas that occurred to me about other types of relationships among components.