Institution
Vignan University
Education•Guntur, Andhra Pradesh, India•
About: Vignan University is a education organization based out in Guntur, Andhra Pradesh, India. It is known for research contribution in the topics: Control theory & CMOS. The organization has 1138 authors who have published 1381 publications receiving 7798 citations.
Topics: Control theory, CMOS, Cement, Machining, Wireless sensor network
Papers
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TL;DR: In this paper, the poly-phase network filter bank multi carrier (PPN-FBMC) waveform is implemented, which reduces the high complexity and computations and simulates FBMC system using Matlab Software, to characterise and analyse the 5G candidate waveform FBMC and compare with OFDM.
Abstract: As the world, is looking for more data speeds along with support for M2M communication in the next generation (5G), the current orthogonal frequency division multiplexing (OFDM) has limitations such as high PAPR, spectrum wastage due to cyclic prefix (CP), out of band (OOB) emissions. To overcome these limitations, 5G researchers is looking for different wave forms and filter bank multi carrier (FBMC) waveform is one of the prime contenders. In this paper, it has been implemented, the poly-phase network filter bank multi carrier (PPN-FBMC), which reduces the high complexity and computations. A prototype filter for the PPN FBMC with high overlapping factors (K = 6 and 8) are implemented. It also simulates FBMC system using Matlab Software, to characterise and analyse the 5G candidate waveform FBMC and compare with OFDM, in terms of error vector magnitude (EVM), peak to average power ratio (PAR), and power spectral density (PSD) performance. The simulated results prove that FBMC outperforms the OFDM systems in all the above mentioned aspects, even under noisy conditions.
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TL;DR: A novel optimization model has been proposed in which the cloud architecture is redefined with new RAM (FeRAM) and other external resources and thus a model OUT_OF_HARDDRIVE method is proposed.
Abstract: Objectives: To fulfil the FeRAM and Cloud infrastructure for the avoidance of external Storage and for IAAS methods. Methods/Statistical Analysis: In this method, we approach with the Eucalyptus Technique and we use node controller to manipulate the exact performance. For interacting with the Device like FeRAM (Ferro Electric RAM) we used Euca2ools for performance statistics. This can be done from the analysis of Cloud Services with the reliable Cloud Controller. Findings: This model deals about the features that can be adopted in the Cloud computing environment along with the Usage of FeRAM's advantages. Our proposal is to adopt all values inside the FeRAM without the usage of Hard Disk. As the storage controller would be having all the patterns to conclude load balancer which simulates our workload along with the scaling listener, it maps with the additionally stored FeRAM. At this point, we would be integration the mechanism involved in the cloud controller and with the FeRAM as this would add more efficient with our works. In future, there will be a need for avoidance of external storage for storing large data. Applications: In this perspective, a novel optimization model has been proposed in which the cloud architecture is redefined with new RAM (FeRAM) and other external resources. Through Internet Connectivity, we make proper authentication and services with secured password protection manner (OTP) or email verification for every login transitions and thus we propose a model OUT_OF_HARDDRIVE method. The resources are provided to the user in the form of connecting bridge as virtual servers and are possibly distributed, running in cloud environment via Internet.
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TL;DR: The results show that the equal error rate (EER), decidability index (DI) and correct recognition rate (CRR) of the proposed approach is better than existing methods for PolyUPalmprint Database.
Abstract: In this paper, palmprint verification and identification with minimum number of features is proposed. The wide principal line extractors (WPLEs) on the region of interest (ROI) are applied to generate wide principal line images (WPLIs). The WPLI is segmented into 2 × 2, 4 × 4, 8 × 8 and 16 × 16 and the feature value is extracted directly from each segment. Experiments are conducted by using the extracted features. The results show that the equal error rate (EER), decidability index (DI) and correct recognition rate (CRR) of the proposed approach is better than existing methods for PolyUPalmprint Database.
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Authors
Showing all 1166 results
Name | H-index | Papers | Citations |
---|---|---|---|
Muthukaruppan Alagar | 40 | 316 | 5914 |
Ebenezer Daniel | 40 | 180 | 5597 |
P. B. Kavi Kishor | 30 | 123 | 3486 |
V. Purnachandra Rao | 26 | 59 | 1723 |
Muddu Sekhar | 24 | 135 | 1929 |
Anandarup Goswami | 23 | 44 | 5427 |
Reddymasu Sreenivasulu | 20 | 58 | 925 |
Murthy Chavali | 20 | 105 | 1699 |
Krishna P. Kota | 20 | 42 | 1172 |
Naveen Mulakayala | 17 | 39 | 937 |
Tondepu Subbaiah | 16 | 65 | 773 |
Bharat Kumar Tripuramallu | 15 | 34 | 574 |
Avireni Srinivasulu | 13 | 97 | 626 |
Abhinav Parashar | 13 | 29 | 375 |
Umesh Chandra | 13 | 39 | 550 |