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Grey wolf express inc12/12/2022 ![]() ![]() In this paper, we use grey wolf optimizer (GWO), which is considered as a meta heuristic algorithm that is prominent in finding global solution. On the other hand, GAs do not give a global solution as all heuristics algorithms that execute blind search and usually stuck on local optima. Thus, most of researchers choose GAs, which are faster and give the same performance as convex algorithms in terms of minimum reconstruction error. Convex algorithms are not efficient because they require high complex computations. The CS reconstruction problems are solved by convex algorithms and greedy algorithms (GAs). ![]() CS provides an alternative new method of compressing data, offering a new signal sampling theory which we can adopt in variety of applications including data and sensor networks ( Cevher & Jafarpour, 2010), medical systems, image processing and video camera, signal detection, analog-to-digital convertors ( Choi et al., 2010) and several other applications. The simulation results show that GWRA significantly exceeds the greedy-based reconstruction algorithms such as sum product, orthogonal matching pursuit, compressive sampling matching pursuit and filtered back projection and swarm based techniques such as BA and PSO in terms of reducing the reconstruction error, the mean absolute percentage error and the average normalized mean squared error.Įxploiting the sparse nature of the signals is highly challenging in various signal processing applications such as signal compression, inverse problems and this motivated the development of compressive sensing (CS) methodologies ( Donoho, 2006). ![]() The effectiveness of GWRA technique is demonstrated and validated through rigorous simulations. GWRA is inspired from the benefits of integrating both the reversible greedy algorithm and the grey wolf optimizer algorithm. In this paper, we propose a new optimization algorithm called grey wolf reconstruction algorithm (GWRA). Greedy-based reconstruction algorithms proved themselves as a good solution to this problem because of their fast implementation and low complex computations. In CS, the most challenging problem is to design an accurate and efficient algorithm for reconstructing the original data. STEEL CABINET THIS SHIPMENT CONTAINS NO SOLID WOOD PACKING MATERIALS SC: 22-4039 FAK PSW HBL NO:WWLLWLC20910668 SCAC CODE:WWLL, FREIGHT PREPAIDįAK PSW SQ:22-4039 SMALL MACHINE DISTILLATION BUCKET FOLDING BED THIS SHIPMENT CONTAIN NO SOLID WOOD PACKING MATERIALS, FREIGHT PREPAID ALL FREIGHT PREPAID (INCLUDE DESTINATION ISPS CFF CONTAINER MAINTENANCE CHARGE) FAX:8621-61322300 TAX ID:91310110748777047E INFO GREATWOLFEXPRESSINC.The recent advances in compressive sensing (CS) based solutions make it a promising technique for signal acquisition, image processing and other types of data compression needs. TIRES THIS SHIPMENT CONTAINS NO SOLID WOOD PACKING MATERIALS HBL NO:WWLLWLC20916473 SCAC CODE:WWLL FREIGHT PREPAIDĬOCONUT CHARCOAL XXINFOGREATWOLFEXPRESSINC.COM XXOP2GREATWOLFEXPRESSINC.COM TRICYCLE THIS SHIPMENT CONTAINS NO SOLID WOOD PACKING MATERIALS S/C:22-4039 FAK PSW HBL NO:WWLLWLC20913163 SCAC CODE:WWLL, FREIGHT PREPAID LOCKER THIS SHIPMENT CONTAINS NO SOLID WOOD PACKING MATERIALS S/C:22-4039 FAK PSW HBL NO:WWLLWLC20909038 SCAC CODE:WWLL, FREIGHT PREPAID ![]()
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