Can Manifold Angle Determine Concavity and Convexity of a Curve?

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In summary, the conversation discusses how to define a function that accounts for concavity and convexity of a curve based on the angle between three consecutive points on the curve. The initial logic of using the sign of a result from substituting an arbitrary point was found to be insufficient in differentiating between concave and convex regions. The idea of using the manifold angle as a basis for determining the nature of the curve is proposed instead. Two functions are suggested, one with a high value in convex regions and a low value in concave regions, and the other with a positive value in concave regions and a negative value in convex regions. The use of the cross product of direction vectors is also mentioned as a way to distinguish between concave and convex
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I have a small query to make regarding concavity and convexity...I have three consecutive points on a curve.and given the angle between the lines joining 1st and 2nd point,2nd and 3rd point respectively.I am supposed to define a function which accounts for concavity and convexity of the curve.It should be a linear function of the angle that is calculated

i tried using equation of the line passing through 1st and 3rd point and had one arbitrary point inside the curve.My logic was that,based on the sign of the result we get by substituting the point number 2 and the arbitrary point,i can determine the concavity and convexity.But this seems to fail in my case as there are points which are close to each other,so,this logic is not able to differentiate properly between a concave and convex side.

instead,i thought of using the manifold angle which was calculated as mentioned in the first few sentences,as the basis to determine the nature of the curve.just wanted to know if this is feasible or not...the function should assume a high value in convex region and small value in concave regions.and one more function to be defined such that it assumes a positive value in concave regions and negative in convex...both should be functions of manifold angle...please help me in sorting this...at least give me an idea of how i can go about it...
 
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If we use the cross product of the direction vectors of the two lines, we get an oriented angle, i.e. its sine value. This allows to distinguishes between concave and convex: greater than 90° or less than 90°. But this isn't linear in the angle. Linearity is in my opinion not necessary and makes geometrically no sense. What should an addition of angles stand for with respect to the curvature? Of course we can add the projection on the sign of the sine value we get, so the outcome is directly concave or convex. But additivity makes still no sense.
 

FAQ: Can Manifold Angle Determine Concavity and Convexity of a Curve?

What is the definition of concavity and convexity?

Concavity and convexity are terms used to describe the shape of a curve or surface. A curve or surface is considered concave if it curves inward, like the inside of a bowl, while it is considered convex if it curves outward, like the outside of a bowl. In mathematical terms, a curve is concave if it has a negative second derivative and convex if it has a positive second derivative.

How are concavity and convexity related to the derivative?

Concavity and convexity are closely related to the second derivative of a function. The second derivative represents the rate of change of the slope of the function. If the second derivative is negative, the function is concave and if the second derivative is positive, the function is convex. This means that the concavity and convexity of a function can be determined by analyzing its second derivative.

What is the significance of concavity and convexity in optimization problems?

In optimization problems, concavity and convexity play a crucial role in determining the nature of the optimal solution. In general, if the objective function is convex, then the optimal solution can be easily found using various optimization techniques. On the other hand, if the objective function is concave, then the optimal solution may be more difficult to find as there may be multiple local maxima or minima.

How do concavity and convexity affect the behavior of a function?

The concavity and convexity of a function can greatly impact its behavior. A convex function will always have a global minimum, meaning it will never decrease indefinitely. On the other hand, a concave function may have multiple local minima, making it more difficult to find the global minimum. Additionally, the rate of change of a convex function will always increase, while the rate of change of a concave function will always decrease.

Can a function be both concave and convex?

No, a function cannot be both concave and convex. This is because a concave function has a negative second derivative, while a convex function has a positive second derivative. Since the second derivative cannot be both positive and negative, a function cannot be both concave and convex at the same time.

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