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Sosnowsky
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Small fixes
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paper/paper.md

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@@ -45,7 +45,7 @@ the underlying dynamics and must be tested against known reference data to ensur
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accuracy.
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`blobmodel` addresses this need by providing a framework for generating synthetic
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datasets resulting from a superposition of uncorrelated pulses [@militello_two-dimensional_2018, @losada_tde_2025]:
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datasets resulting from a superposition of uncorrelated pulses [@militello_two-dimensional_2018; @losada_tde_2025]:
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$$
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\Phi(x,y,t) = \sum_{k=1}^{K} a_k \varphi\left( \frac{x-v_k(t-t_k)}{\ell_{x, k}}, \frac{(y-y_k)-w_k(t-t_k)}{\ell_{y, k}}\right) ,
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$$
@@ -55,14 +55,13 @@ Additionally, each pulse may be tilted an angle given by an additional random va
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$\theta_k$ with respect to its centre.
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The framework allows an explicit definition of all relevant process parameters, including:
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* All pulse parameters if defined as degenerate random variables.
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* All distribution functions of the pulse parameters otherwise.
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* Optionally, a drainage term $\tau_\shortparallel$ that models an exponential decay in the pulse amplitude.
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* Spatial and temporal resolution.
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* Degree of pulse overlap.
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* Signal length.
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For more details visit [blobmodel's documentation](https://blobmodel.readthedocs.io/en/latest/)
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- All pulse parameters if defined as degenerate random variables.
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- All distribution functions of the pulse parameters otherwise.
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- Optionally, a drainage term $\tau_\shortparallel$ that models an exponential decay in the pulse amplitude.
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- Spatial and temporal resolution.
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- Degree of pulse overlap.
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- Signal length.
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This allows researchers to systematically test and benchmark
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tracking algorithms and velocity estimation techniques in a controlled setting.
@@ -72,6 +71,8 @@ formation of moving structures in one or two-dimensional space. By offering an o
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and easily accessible tool, blobmodel supports the development and validation of
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analysis methods used in experimental and computational research.
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For more details visit [blobmodel's documentation](https://blobmodel.readthedocs.io/en/latest/).
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The package has been used to generate synthetic data to study and compare the robustness of
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velocity estimation techniques on coarse-grained imaging data [@losada_three-point_2024].
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