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  2. Residuated mapping - Wikipedia

    en.wikipedia.org/wiki/Residuated_mapping

    If B is a poset, the set of functions A → B can be ordered by the pointwise order f ≤ g ↔ (∀x ∈ A) f(x) ≤ g(x).. It can be shown that a monotone function f is residuated if and only if there exists a (necessarily unique) monotone function f +: B → A such that f o f + ≤ id B and f + o f ≥ id A, where id is the identity function.

  3. File:Fractional Residual Variances comparison, PCA and NMF.pdf

    en.wikipedia.org/wiki/File:Fractional_Residual...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  4. ecu.test - Wikipedia

    en.wikipedia.org/wiki/Ecu.test

    ecu.test automates the control of the whole test environment and supports a broad range of test tools. Various abstraction layers for measured quantities allow its application on different testing levels, e.g. within the context of model in the loop, software in the loop and hardware in the loop as well as in real systems (vehicle and driver in the loop).

  5. Residual neural network - Wikipedia

    en.wikipedia.org/wiki/Residual_neural_network

    A residual neural network (also referred to as a residual network or ResNet) [1] is a deep learning architecture in which the layers learn residual functions with reference to the layer inputs. It was developed in 2015 for image recognition , and won the ImageNet Large Scale Visual Recognition Challenge ( ILSVRC ) of that year.

  6. MOOSE (software) - Wikipedia

    en.wikipedia.org/wiki/MOOSE_(software)

    A key design aspect of MOOSE is the decomposition of weak form residual equations into separate terms that are each represented by compute kernels. The combination of these kernels into complete residuals describing the problem to be solved is performed at run time.

  7. Residual (numerical analysis) - Wikipedia

    en.wikipedia.org/wiki/Residual_(numerical_analysis)

    When one does not know the exact solution, one may look for the approximation with small residual. Residuals appear in many areas in mathematics, including iterative solvers such as the generalized minimal residual method, which seeks solutions to equations by systematically minimizing the residual.