Two-dimensional speckle tracking methods have shown great promise in imaging tissue motion and deformations in the vicinity of blood vessels offering the promise of new methods for detecting and staging of vascular disease. However, vessel wall echo reverberations overwhelm the echoes (scattering) from the blood and result in loss of flow information in large regions within the vessel. In this paper, we present a de sign approach for a time-varying dereverberation inverse filter for echo data within the vessel. The design approach is motivated by the fact that the reverberation pattern varies significantly with the pulsatory motion of the vessel wall. Minute changes in the location/orientation of the vessel wall with respect to the imaging beam result in measurable changes in the speckle-specular echo mixture at the vessel wall and the observed periodicities in the reverberation pattern within the vessel. Therefore, a time-varying inverse filter is necessary to remove the reverberation components appropriately during the heart cycle. A maximum likelihood approach for optimizing the inverse filter parameter is presented. The performance of the dereverberation algorithm is illustrated using pulse-echo data from realtime imaging of the carotid artery of a healthy volunteer.

Phase-locked loops (PLLs) are widely used in electronic systems. As PLL malfunction is one of the most important factors in re-fabs of SoCs, fast simulation of PLLs to capture non-ideal behavior accurately is an immediate, pressing need in the semiconductor design industry. In this paper, we present a nonlinear macromodel based PLL simulation technique that is considerably more accurate than prior linear PLL simulation techniques. Our method is able to accurately capture transient behavior and faithfully estimate timing jitter in noisy PLLs. We demonstrate the proposed technique on ring and LC voltage-controlled oscillator (VCO) based PLLs, and compare results against linear PLL macromodels and full SPICE-level simulation. We show that, unlike prior linear macromodel based approaches, the proposed nonlinear technique captures the dynamics of complex phenomena such as locking, cycle slipping and power supply noise induced PLL jitter, replicating qualitative features from full SPICE simulations accurately while providing speedups of over two orders of magnitude.

Linear periodically time-varying (LPTV) abstractions are useful for a variety of communication and computer subsystems. In this paper, we present a novel operator-based model-order reduction (MOR) algorithm for reducing large LPTV systems to smaller ones, a capability useful for system-level performance analysis. Our pro-cedure is based on generalizing existing matrix-based Krylov-sub-space algorithms to arbitrary function-space operators. Practical benefits of our approach include significantly enhanced algorithm and code modularity, compared to previous LPTV-MOR approaches based on a-priori discretization. We demonstrate the use of the pro-posed technique on several circuit examples.