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The sensitivity shaping problem is reduced to a finite-dimensional constrained nonlinear least-squares optimization problem.
The proposed approach is applied to address the thermal spatiotemporal dynamic shaping problem in a tubular chemical reactor.
A sensitivity shaping problem is formulated as an approximation problem to the desired frequency response with a function in a class of sensitivity functions with a degree bound.
The dynamic shaping problem is addressed via error dynamics regulation between the governing PDE and a target PDE which describes the desired spatiotemporal behavior.
After discretization the evolutionary state problem, associated with the optimal shape problem, is formulated as a sequence of nonsmooth equations and a general form of the optimal design problem is treated by using a nonsmooth approach.
Adding more exponential terms does not solve the curve shape problem.
As Fig. 2 clearly shows, not controlling for time trends resulted in bias, with the non-V-shape problem.
VisNet solves the shape problem by implementing a feature hierarchy in which combinations of features in the correct spatial relationship become learned at every stage of the processing, resulting in shape not low-level feature recognition (Rolls 1992, 2008, 2012a; Elliffe et al. 2002).
It focuses on the ways that the implementation of complex interventions is shaped by problems of workability and integration.
This paper addresses a novel constrained decentralized shaping control problem for a class of nonlinear large-scale interconnected distribution systems.
The literature suggests that social environmental factors help shape adolescent problem behaviour.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com