National Institute of Technology, Karnataka

About: National Institute of Technology, Karnataka is a education organization based out in Mangalore, Karnataka, India. It is known for research contribution in the topics: Corrosion & Cloud computing. The organization has 5017 authors who have published 7057 publications receiving 70367 citations.

Multilevel thresholding based on Chaotic Darwinian Particle Swarm Optimization for segmentation of satellite images

Abstract: This paper introduces an improved variant of Darwinian PSO algorithm based on chaotic functions.It replaces random sequences by chaotic sequences mitigating the problem of premature convergence.Efficiency of 10 defined chaotic maps are investigated and the best one was chosen.The proposed algorithm is compared with five different chaotic variants of existing optimization algorithms.It provides better convergence characteristics and segmentation results as compared with existing algorithms. This paper proposes an improved variant of Darwinian Particle Swarm Optimization algorithm based on chaotic functions. Most of the evolutionary algorithms faces the problem of getting trapped in local optima in its search for global optimum solutions. This is highly influenced by the use of random sequences by different operators in these algorithms along their run. The proposed algorithm replaces random sequences by chaotic sequences mitigating the problem of premature convergence. Experiments were conducted to investigate the efficiency of 10 defined chaotic maps and the best one was chosen. Performance of the proposed Chaotic Darwinian Particle Swarm Optimization (CDPSO) algorithm is compared with chaotic variants of optimization algorithms like Cuckoo Search, Harmony Search, Differential Evolution and Particle Swarm Optimization exploiting the chosen optimal chaotic map. Various histogram thresholding measures like minimum cross entropy and Tsallis entropy were used as objective functions and implemented for satellite image segmentation scenario. The experimental results are validated qualitatively and quantitatively by evaluating the mean, standard deviation of the fitness values, PSNR, MSE, SSIM and the total time required for the execution of each optimization algorithm.

An Improved Seven-Level PUC Inverter Topology With Voltage Boosting

Abstract: In this brief, a seven-level (7L) improved packed U-cell (IPUC) inverter with reduced power electronic components is proposed. The presented IPUC inverter has low voltage stress on switches and is capable of voltage boosting. A new voltage balancing method based on logic form equations is developed for regulating the inherent floating capacitor voltage to half the input dc voltage. The proposed 7L IPUC is compared with other state-of-the-art 7L inverters in terms of number of IGBTs, blocking voltage, and driver circuits for attesting its superior merits. The performance of the proposed voltage balancing is verified through a laboratory prototyped 7L IPUC inverter considering varying load conditions and the corresponding results are elucidated.