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The balanced scorecard is a performance measurement matrix designed to capture financial and non-financial metrics that provide insight into the critical success factors for an organization, effectively aligning organization strategy to key performance objectives.
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We consider the optimization of these two cases as measurement matrix design for 1D-CS model.
The measurement matrix design for all cases was proposed based on minimizing MC of sensing matrix using gradient descent algorithm.
Figure 9 shows the runtime of measurement matrix design for different methods versus the number of measurements.
Recently, some measurement matrix design methods have been proposed based on minimizing the MC of the sensing matrix [29 31].
Figure 3 shows the convergence curve of this algorithm for our proposed measurement matrix design for 500 Monte Carlo runs.
In Section 4, we propose a measurement matrix design for 1D and 2D CS model using gradient decent algorithm.
Then, we divided the measurement matrix design into four cases in which the measurement matrices applied to receivers and pulses can be equal or different.
Fig. 9 Comparison of runtime of measurement matrix design for different methods versus the number of measurements in CS MIMO radar.
(2) Random measurement matrix design: It is important to make a sensing matrix which allows recovery of as many entries of unknown signal as possible by using as few measurements as possible.
In this paper, we propose a measurement matrix design that improves the parameter estimation of an extended target in a compressive sensing multiple-input multiple-output (CS-MIMO) radar system.
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