More particularly, three probability-based optimization methods have been proposed to optimize the mutual coherence of measurement matrix called Sequential Cross-Entropy (SCE), Extended Estimating of Distribution Algorithm (EEDA), and Parallel Cross-Entropy (PCE).
By exploiting the EMV features, introducing a circle cluster, and proposing a novel coherence-pattern, we then form a feature-aided weight coherence (FAWC) optimization to optimize measurement-matrix.
Since there is no known polynomial time approach to optimize RIP, alternatively, the mutual coherence is minimized which is more practical [10].
Hence, the object is to optimize that will minimize the mutual coherence.
Then, a feature-aided weight coherence (FAWC) optimization, based on the algorithm of weighted coherence minimization (WCM) [22], is developed to optimize measurement-matrix without computational complexity increasing.
In this paper, aiming at minimizing the mutual coherence, a method is proposed to optimize the projection matrix.
Accordingly, an ESBMV-SCBP beamformer was proposed in this paper, which used the coherence of the subarray signal to compute an SCBP to optimize the ESBMV results.
The objective is to optimize an initially random measurement matrix to a matrix which presents a smaller coherence than the initial one.
To optimize the process, a "selective" warping technique is proposed that takes the advantage of temporal coherence to reduce the computational overhead.
Maintaining coherence between system functional, performance, production and operational requirements is a key to the ability to optimize the design of large-scale systems.
Ashima is trying to optimize.
