What's The Discrete Math Derivative Equivalent?

In summary, the conversation discusses determining the base value b that yields a value ƒ closest to I, given certain constraints. These constraints include choosing a base value b, and finding a combination of b and n that maximizes b^n while staying under the value of I. The conversation also suggests using a formula to narrow down the search space for possible values of b and n.
  • #1
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$$ƒ = b^n$$
$$ b,n,I ∈ ℤ $$

Condition: Upon choosing a base value [itex]b[/itex]..

$$ n | b^n ≤ I $$
(n is determined based off the value of [itex]b[/itex] to yield the highest ƒ without going over [itex]I[/itex])
$$1<b<L , L<<I$$
where [itex]I[/itex] is some large number, and [itex]L[/itex] is also sufficiently large such that we want to avoid going through each base integer via trial and error...

How might I determine the base value that yields a value [itex]ƒ[/itex] that is closest to [itex]I[/itex]?
 
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  • #2
I'm not sure exactly what you are asking.
Are you asking how to, given ##L,I\in\mathbb{Z}## with ##0<<L<<I##, find the combination ##b,n\in\mathbb{Z}## that maximizes ##b^n## subject to the constraints
1. ##1<b<L##; and
2. ##b^n<I##

If so then you could set ##Hi=\lfloor\log_2 I\rfloor## and ##Lo=\lceil \log_L I\rceil##, then find
$$b^n=max_{Lo\leq m\leq Hi}\bigg( \lfloor I^\tfrac{1}{m}\rfloor\bigg)^m$$

where ##n## is the value of ##m## that delivers that maximum.
That will give a much smaller search space than ##1,...,L##.
 
Last edited:

Related to What's The Discrete Math Derivative Equivalent?

1. What is the definition of the discrete math derivative equivalent?

The discrete math derivative equivalent is a mathematical concept that calculates the rate of change of a discrete function over a finite interval. It is similar to the concept of a derivative in calculus, but instead of calculating the instantaneous rate of change, it calculates the average rate of change over a finite interval.

2. How is the discrete math derivative equivalent calculated?

The discrete math derivative equivalent is calculated by taking the difference between the function values at two points and dividing it by the difference in the independent variable (x) values. This can be represented as (f(x2) - f(x1)) / (x2 - x1), where x2 and x1 are two points on the function.

3. What is the importance of the discrete math derivative equivalent in mathematics?

The discrete math derivative equivalent is important in mathematics because it allows us to analyze the behavior of discrete functions and make predictions about their future values. It is also used in statistics and data analysis to analyze trends and patterns in discrete data.

4. Can the discrete math derivative equivalent be used for all types of discrete functions?

Yes, the discrete math derivative equivalent can be used for all types of discrete functions, including linear, quadratic, exponential, and logarithmic functions. However, it is important to note that the results may not always be accurate for functions with sharp changes or discontinuities.

5. How is the concept of the discrete math derivative equivalent applied in real-world scenarios?

The discrete math derivative equivalent can be applied in various real-world scenarios, such as analyzing stock market trends, predicting population growth, and predicting the spread of diseases. It is also used in computer science and engineering to analyze and optimize algorithms and processes.

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