Abstract: Issues related to creation of mathematical models and modeling of pre-formation of random processes, signals and noise in non-linear non-inertial elements were analyzed. The models were ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the ...

Researchers present new experimental and theoretical results for the bound electron g-factor in lithium-like tin which has a much higher nuclear charge than any previous measurement. The experimental ...

Researchers from the Max-Planck-Institut fuer Kernphysik present new experimental and theoretical results for the bound ...

The strategy for encoding Petri nets as chained linear lists involves two structures: one for PList placements and one for TList transitions. This is the orthogonal representation of chained linear ...

Doom: The Dark Ages offers a refreshing take on the franchise, blending medieval aesthetics with classic Doom gameplay. It ...

Warner Bros. Discovery's Jamie Cooke unpacks the future of streaming in MENA and offers essential takeaways for brands and ...

According to the superposition principle of electromagnetic field, a set of linear equations concerning the element signals are created with the measured array signals. With the scattering parameters ...

Indeed, if the uncertainty is great enough, the optimal level of reserves can exceed the cutoff for abundant reserves under no uncertainty. That is, uncertainty can imply that it is optimal to supply ...

But he systematically set out word-­form linear and quadratic equations, with algorithmic methods for solving them — that is, for finding the "unknown numbers," our modern x's and y's.

This gives an approximate local description of the physics by a set of simple linear (but sometimes nonlinear) equations. When the contributions from all elements are assembled you end up with a ...