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E-learning systems usually require many hardware and software resources.
Micro-autonomous systems usually require large force, large displacement and less power consumption.
Parameters estimated for solving dynamical systems usually require certain time to converge and need to be smoothed by a dedicated algorithms.
Data acquisition systems usually require anti-aliasing low-pass filters as well as low-pass noise filters in their preceding signal conditioning stages.
Although underactuated systems usually require nonlinear controllers, the easy tuning and understanding of linear controllers make them more attractive for designers and final users.
Both systems usually require a p-value of less than 0.001.
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Modeling large systems usually requires metamodels or response surfaces (RSs) of sub-systems.
Moreover, stability analysis for non-autonomous systems usually requires specific and quite different tools from the autonomous ones (systems with constant coefficients).
Implementation of SC-FDE in multiple-input multiple-output (MIMO) systems usually requires, in advance, the channel information in terms of the channel frequency response (CFR).
Development of complex robotics systems usually requires tools and software frameworks such as the WillowGarage Robot Operating System (ROS) to ease code integration and reuse tasks.
However, the use of these systems usually requires the adoption of a high threshold value to avoid the inclusion of impostor patterns into the genuine biometric reference.
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