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1h
comment Efficient method to calculate passes (rises and sets) for satellites
"There is a function describing the characterisic elevation of ISS seen from an observers horizon." Well, can you tell us what that function is? Also, it looks like your graph does not have enough sampling: the peak at about 16:00:00 is underresolved.
13h
comment Is it true that a quasiconvex, increasing and continous function, is convex?
What does $x\ge y$ mean when $x,y\in\mathbb R^n$?
13h
comment *SOLVED* Largest lower bound that covers p percent of the data
The only subset which matters is the top $p\%$ of $X$. So: sort the numbers, take the top $p\%$, and return the smallest of them.
1d
comment Clouds Filter like in Photoshop formula
It's almost certainly Perlin noise. Take a look at Ken Perlin's slides about it.
2d
comment What does “two polynomials have no zeros in common” mean?
It means that there is no value which is a zero of both polynomials.
Nov
23
comment 0 to the power of 0, what does the essential discontinuity actually look like?
It doesn't make sense to plot $x^y$ when $x$ is negative. Try setting the range of $x$ to $[0,2]$.
Nov
23
comment Normalizing Vectors to get short numbers
What do you mean that when you normalize the result "the numbers are still long"? The components will all be bounded between $-1$ and $1$.
Nov
22
comment The Stupid Computer Problem : can every polynomial be written with only one $x$?
@Steven: Unsolvable quintics don't become solvable even if we allow exponentiation and logarithms in the solution, do they?
Nov
21
comment Continuum Approach to Modeling Cell Proliferation and Differentiation (PDE)
What's interesting is that the two terms on the left side of the PDE comprise the advection equation, which one can interpret as saying that the cells move towards increasing $\lambda$ at a rate of $\delta$ per unit time. So if you initially had say $10$ cells at $\lambda=0$ and $5$ cells at $\lambda=0.1$, after time $t$ you'd have $10$ cells at $\lambda=\delta t$ and $5$ at $\lambda=0.1+\delta t$ (ignoring birth and death). If this sounds reasonable, I can write a answer explaining how this arises from the PDE later.
Nov
21
comment Continuum Approach to Modeling Cell Proliferation and Differentiation (PDE)
I think this is a very good and on-topic question about how to understand and interpret a particular differential equation. I don't know if it makes sense to think of $X$ in terms of A cells and B cells though -- in the original PDE, $X$ is both a function of $t$ and $\lambda$, so at any given time $t$ you have a different $X$ value at all values of $\lambda$ from $0$ to $1$. To me this suggests thinking of the situation as a distribution of cells with different $\lambda$'s, but I don't know if that is makes biological sense.
Nov
21
comment Proof that no Eulerian Tour exists for graph with even number of vertices and odd number of edges
For the question in the first sentence, not the question in the title: assume all the vertices have even degree, use the handshaking lemma, and check divisibility by $4$.
Nov
21
comment Probability to find connected pixels
@daOnlyBG: There's no need to change British spellings to American ones.
Nov
21
comment norm over differentiable functions computable from derivatives only
What does norm mean here? Is the function $f$ vector-valued and you are minimizing the vector norm $\|f(x_{1,\ldots,6})-\hat f\|_2$, or something else?
Nov
21
comment Intuitive Explanation of Bessel's Correction
This is a misleading explanation. If you pick a small sample, you expect to get a small spread, but you'll divide by the size of the sample in the end anyway, so that's not a reason for the resulting sample variance to be smaller. Indeed, your argument would still apply if you computed the variance with respect to the true population mean, but in this case the expected sample variance is equal to the population variance.
Nov
21
comment Use of Delaunay Triangulation and Voronoi Diagram to find alpha shape using Edelsbrunner's algorithm
If your question is "please explain the whole alpha-shape algorithm to me" then it may be too broad in scope for this site. You will be more likely to get help if you can narrow your question down to a specific part that you do not understand.
Nov
21
comment Distribute small number of points on a disc
As you are aware, there are many possible optimization criteria, and they may yield different optimal configurations. It's not possible to say which one is "the best"; different criteria will be useful for different purposes.
Nov
20
comment Most ambiguous and inconsistent phrases and notations in maths
I feel like your answer needs a little more justification. Right now you've shown that uses of the term "trivial" are broad but not that they are ambiguous. To me they all fall under the umbrella of "nothing much to it": the "nothing much" in the colloquial usage being in terms of effort, while in the mathematical uses, it is "nothing much" in terms of structure or complexity.
Nov
19
comment How to find fitting parameters of the function?
You could do worse than to start by checking the Wikipedia page for nonlinear least squares, which is basically what you are doing. The Gauss-Newton and Levenberg-Marquardt algorithms are popular numerical methods for such problems.
Nov
17
comment Convex sets in $\mathbb R^n$: Do they have a particular form ? Does the gradient of a linear convex function $f$ exist on such a set?
Is $S$ necessarily some ball or a Cartesian product of intervals? Not at all, see the first illustration on Wikipedia.
Nov
14
comment Random Sampling of vectors on the Complex Unit Sphere
Ah, in that case, it's geometrically equivalent to the unit sphere in $\mathbb R^{2n}$ because $\mathbb C\cong\mathbb R^2$. So you just have to sample from a real unit sphere and interpret the result as a vector in $\mathbb C^n$. In fact, since it's a one-liner in Mathematica, here you go: ({1, I}.#) & /@ Partition[Normalize@RandomVariate[NormalDistribution[], 2 n], 2]