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In this paper, an optimal approach for the design of 6-T FinFET-based SRAM cells is proposed. The approach considers the statistical distributions of gate length and silicon thickness and their corresponding statistical correlations due to process variations. In this method, a back-gate voltage is used as the optimization knob. With the help of particle swarm optimization (PSO), the back-gate voltages that maximize the yield of the SRAM array against read, write, and access time failures are found. It will be shown that, with this method, a very high yield is achieved. [ABSTRACT FROM AUTHOR]

A perfusion phantom with unique features and a wide variety of applications in magnetic resonance imaging (MRI) and other imaging modalities is presented. Using microfabrication technique, a network of microchannels, in the scale of actual microvasculature, was created. The geometry of the network was determined based on Murray's “minimum work” law to simulate the hemodynamic in actual capillary networks. The perfusion-related parameters, such as flow, volume ratio, and the transit time, were precisely calculated using a finite-element method based program. These parameters were also estimated through the deconvolution of the residue function from the tissue concentration–time curve in the perfusion model. The widely accepted singular value decomposition (SVD) method in standard sSVD and reformulated rSVD forms were used for the purpose of the deconvolution and regularization. The accuracy of these methods in the presence of delay and dispersion was investigated. Comparing the estimated values to the true values, the contribution of each of these sources of error to the total error in the estimated perfusion parameters was determined. [ABSTRACT FROM PUBLISHER]