Reduced common-mode voltage operation of a new seven-level hybrid multilevel inverter topology with a single DC voltage source

In this study, analysis of extending the linear modulation range of a zero common-mode voltage (CMV) operated n-level inverter by allowing reduced CMV switching is presented. A new hybrid seven-level inverter topology with a single DC supply is also presented in this study and inverter operation for zero and reduced CMV is analysed. Each phase of the inverter is realised by cascading two three-level flying capacitor inverters with a half-bridge module in between. Proposed inverter topology is operated with zero CMV for modulation index <86% and is operated with a CMV magnitude of V-dc/18 to extend the modulation range up to 96%. Experimental results are presented for zero CMV operation and for reduced common voltage operation to extend the linear modulation range. A capacitor voltage balancing algorithm is designed utilising the pole voltage redundancies of the inverter, which works for every sampling instant to correct the capacitor voltage irrespective of load power factor and modulation index. The capacitor voltage balancing algorithm is tested for different modulation indices and for various transient conditions, to validate the proposed topology.

Low Resolution Face Recognition Across Variations in Pose and Illumination

We propose a completely automatic approach for recognizing low resolution face images captured in uncontrolled environment. The approach uses multidimensional scaling to learn a common transformation matrix for the entire face which simultaneously transforms the facial features of the low resolution and the high resolution training images such that the distance between them approximates the distance had both the images been captured under the same controlled imaging conditions. Stereo matching cost is used to obtain the similarity of two images in the transformed space. Though this gives very good recognition performance, the time taken for computing the stereo matching cost is significant. To overcome this limitation, we propose a reference-based approach in which each face image is represented by its stereo matching cost from a few reference images. Experimental evaluation on the real world challenging databases and comparison with the state-of-the-art super-resolution, classifier based and cross modal synthesis techniques show the effectiveness of the proposed algorithm.