We develop an efficient MRI denoising algorithm based on sparse representation and curvelet transform with variance stabilizing transformation framework. By using sparse representation, a MR image is decomposed into a sparsest coefficients matrix with more no of zeros. Curvelet transform is directional in nature and it preserves the important edge and texture details of MR images. In order to get sparsity and texture preservation, we post process the denoising result of sparse based method through curvelet transform. To use our proposed sparse based curvelet transform denoising method to remove rician noise in MR images, we use forward and inverse variance-stabilizing transformations. Experimental results reveal the efficacy of our approach to rician noise removal while well preserving the image details. Our proposed method shows improved performance over the existing denoising methods in terms of PSNR and SSIM for T1, T2 weighted MR images.
Winding function theory has been successfully applied for the calculation of magnetizing inductances of asynchronous and synchronous rotating machines for steady-state and transient analysis. The computational burden in such simulations is heavy because of the calculation of a large number of inductances of the stator and rotor circuit coils, at every time step, each of which requires evaluation of definite integrals of the products of winding functions, their distributions and inverse air gap functions around the rotor periphery. This article proposes a modified discrete space model of continuous space winding function of a squirrel cage induction motor. The discrete model uses the air gap functions directly and consequently eliminates inverse air gap functions and their approximations. Further, it uses simple and direct formulae for the calculation of motor inductances, which results in considerable reduction in the computational complexity and execution time while preserving the accuracy of computation. Discrete winding functions are suitable for the simulation of gradual changes in asymmetrical faults such as eccentricity, rotor bar faults and end ring faults in a three phase squirrel cage induction motor. Simulation results show the comparative assessment of computational complexity, accuracy and execution time required for the calculation of the stator and rotor inductance values of an asymmetrical induction motor.
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