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Currently (see [1]) if a state space system has eigenvalues at 0, it will return a scalar NaN for DC gain:
```python
except LinAlgError:
# zero eigenvalue: singular matrix
…
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Currently, there are no guarantees about ordering of eigenvalues and singular vectors returned by nalgebra's decompositions. A common convention throughout mathematical literature is to assume that ei…
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Principal component analysis (PCA) gives a handle to calculate the direction and degree of anisotropy in a 2D scattering image. It can be performed based on a Singular Value Decomposition (SVD) of the…
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This is an unexpected shape from the POD output, therefore I am not sure what is in the V matrix which is critical for interpreting results of DMD.
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Imported from SourceForge on 2024-07-05 21:40:36
Created by **[sueyllam](https://sourceforge.net/u/sueyllam/)** on 2011-11-09 23:52:45
Original: https://sourceforge.net/p/maxima/bugs/2292
---
Since …
rtoy updated
4 months ago
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I have some doubts about the correctness of the implementation of Singular Value Decomposition.
Take f.e. this input matrix/tensor:
{{6,3,-3},{-3,3,6},{-3,-6,-3}}
WolframAlpha and numpy will …
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Would you have any suggestion regarding a more efficient clustering method?
I asked Mistral AI and was informed about:
Distance-based methods: These methods measure the similarity between time …
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> 82. Compute a matrix rank (★★★)
> hint: np.linalg.svd
>
> \# Author: Stefan van der Walt
>
> Z = np.random.uniform(0,1,(10,10))
> U, S, V = np.linalg.svd(Z) # Singular Value Decomposition
>…
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Dear geomstats team,
we are trying to perform geodesic regression in Kendall shape space but encountered the issue that the current implementation is not compatible with autodiff functionality.
In…
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Hi!
I need a Takagi factorization for a project I am working on, so I tried to use your package. However, in some cases it fails and I don't know why. Here is an example:
I start with a symmetric …