In today’s digital era, developing digital circuits is bounded by the research towards investigating various nano devices. This paper provides the design of compact Baugh-Wooley multiplier using reversible logic. Eve...In today’s digital era, developing digital circuits is bounded by the research towards investigating various nano devices. This paper provides the design of compact Baugh-Wooley multiplier using reversible logic. Even though various researches have been done for designing reversible multiplier, this work is the first in the literature to use Baugh-Wooley algorithm using reversible logic. In this work, a new 5 × 5 reversible multiplier cell is proposed which will be useful in designing Baugh-Wooley multiplier. The proposed single multiplier cell is able to perform addition of a 1 × 1 product with the sum and carry from the previous cell. This reversible multiplier cell is useful in building up regularity in the array multipliers. The Toffoli gate synthesis of the proposed reversible multiplier cell is also given.展开更多
Neuro-imaging techniques are used to extract and assess brain enactments. As brain activations are free to advance in an eccentric way, data driven methods are exploited for functional localization. Three motor imbala...Neuro-imaging techniques are used to extract and assess brain enactments. As brain activations are free to advance in an eccentric way, data driven methods are exploited for functional localization. Three motor imbalance subjects whose scan size were 128 × 128 × 23 and an aggregate of 110 volumes joined by three scans for nine acquisitions, who are on a normal age of 65 years and a set of 10 subject’s simulated data was subjected to examination. To fully exploit the potential, advanced signal processing methods are applied on acquired resting state functional MRI (rsfMRI) and SimTB simulated rsfMRI. An algorithm called Independent Component Analysis-Particle Swam Optimization two-class classifier for decision support is implemented. The algorithm pre-process each simulated and real time rsfMRI scans, extract independent components(IC) from smoothed output, select eigen vector for optimized minimum misclassification from both time series data and perform 2-class classification using k-means clustering. The proposed algorithm aided the classification of about 87.5% of the functional localization of shaky hand subjects of acquired rsfMRI data. The number of highly activated voxels in the sensory motor network is more in shaky hand subjects.展开更多
文摘In today’s digital era, developing digital circuits is bounded by the research towards investigating various nano devices. This paper provides the design of compact Baugh-Wooley multiplier using reversible logic. Even though various researches have been done for designing reversible multiplier, this work is the first in the literature to use Baugh-Wooley algorithm using reversible logic. In this work, a new 5 × 5 reversible multiplier cell is proposed which will be useful in designing Baugh-Wooley multiplier. The proposed single multiplier cell is able to perform addition of a 1 × 1 product with the sum and carry from the previous cell. This reversible multiplier cell is useful in building up regularity in the array multipliers. The Toffoli gate synthesis of the proposed reversible multiplier cell is also given.
文摘Neuro-imaging techniques are used to extract and assess brain enactments. As brain activations are free to advance in an eccentric way, data driven methods are exploited for functional localization. Three motor imbalance subjects whose scan size were 128 × 128 × 23 and an aggregate of 110 volumes joined by three scans for nine acquisitions, who are on a normal age of 65 years and a set of 10 subject’s simulated data was subjected to examination. To fully exploit the potential, advanced signal processing methods are applied on acquired resting state functional MRI (rsfMRI) and SimTB simulated rsfMRI. An algorithm called Independent Component Analysis-Particle Swam Optimization two-class classifier for decision support is implemented. The algorithm pre-process each simulated and real time rsfMRI scans, extract independent components(IC) from smoothed output, select eigen vector for optimized minimum misclassification from both time series data and perform 2-class classification using k-means clustering. The proposed algorithm aided the classification of about 87.5% of the functional localization of shaky hand subjects of acquired rsfMRI data. The number of highly activated voxels in the sensory motor network is more in shaky hand subjects.
