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Recently, some measurement matrix design methods have been proposed based on minimizing the MC of the sensing matrix [29 31].
In this paper, we compare two different risk matrix design methods from the perspective of applicability.
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This paper proposes a projection matrix design method using the support set of the sparse signal estimated via previous measurements.
Figure 9 shows the runtime of measurement matrix design for different methods versus the number of measurements.
Fig. 9 Comparison of runtime of measurement matrix design for different methods versus the number of measurements in CS MIMO radar.
New relaxed conditions and linear matrix inequality-based design methods are proposed that allow outperforming previous found in the literature.
Moreover, this paper shows that the computational problem of finding the controllers with the new degree bound is convex by providing two linear matrix inequality-based design methods (algorithms) for constructing the reduced-order controllers.
By using the Lyapunov stability theory and the matrix technology, the design method of the desired filter is given in terms of a matrix inequality which can be solved by using the available software.
Axiomatic design and design structure matrix (DSM) are two popular design methods at the moment, while most related researches only apply the basic ideas of axiomatic design or DSM to some use cases.
Observation and evaluation results from a Usability Context Analysis (UCA) was used to improve the analysis of Strengths, Weaknesses, Opportunities and Threats (SWOT Analysis) and the matrix of Threats, Opportunities, Weaknesses, and Strengths (TOWS matrix), resulting in two assistive device design methods named AD-SWOT and AD-TOWS.
Furthermore, the full matrix centralized controller design method proposed in this paper is applicable to high dimensional multivariable systems with satisfactory performance.
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