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<span lang="EN-US">In this work, differential evolution based compressive sensing technique for detection of faulty sensors in linear arrays has been presented. This algorithm starts from taking the linear measurements of the power pattern generated by the array under test. The difference between the collected compressive measurements and measured healthy array field pattern is minimized using a hybrid differential evolution (DE). In the proposed method, the slow convergence of DE based compressed sensing technique is accelerated with the help of parallel coordinate decent algorithm (PCD). The combination of DE with PCD makes the minimization faster and precise. Simulation results validate the performance to detect faulty sensors from a small number of measurements.</span>
Linear Array Synthesis, Economics, Wireless Energy Harvesting and Information Transfer, Antenna (radio), Computational Mechanics, Aerospace Engineering, FOS: Mechanical engineering, Optimization Techniques for Antenna Arrays, Span (engineering), Antenna array, Quantum mechanics, TK Electrical engineering. Electronics Nuclear engineering, Phased Array Antennas, Sparse Approximation, Engineering, Compressed Sensing, FOS: Electrical engineering, electronic engineering, information engineering, Civil engineering, Electrical and Electronic Engineering, Antenna Arrays, Economic growth, Minification, Physics, Power (physics), Theory and Applications of Compressed Sensing, Computer science, Programming language, Algorithm, Physical Sciences, Convergence (economics), Telecommunications, Compressed sensing, Thermodynamics, Differential (mechanical device), Differential evolution, FOS: Civil engineering
Linear Array Synthesis, Economics, Wireless Energy Harvesting and Information Transfer, Antenna (radio), Computational Mechanics, Aerospace Engineering, FOS: Mechanical engineering, Optimization Techniques for Antenna Arrays, Span (engineering), Antenna array, Quantum mechanics, TK Electrical engineering. Electronics Nuclear engineering, Phased Array Antennas, Sparse Approximation, Engineering, Compressed Sensing, FOS: Electrical engineering, electronic engineering, information engineering, Civil engineering, Electrical and Electronic Engineering, Antenna Arrays, Economic growth, Minification, Physics, Power (physics), Theory and Applications of Compressed Sensing, Computer science, Programming language, Algorithm, Physical Sciences, Convergence (economics), Telecommunications, Compressed sensing, Thermodynamics, Differential (mechanical device), Differential evolution, FOS: Civil engineering
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