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The strong interaction between Electronic Design Automation (EDA) tools and Complementary Metal-Oxide Semiconductor (CMOS) technology contributed substantially to the advancement of modern digital electronics. The continuous downscaling of CMOS Field Effec ...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. Quantum tunneling provides a different mechanism for moving between states, with the potential for reduced time scales and different outcomes. Thermal and q ...
We prove that if one can predict any of the bits of the input to an elliptic curve based one-way function over a finite field, then we can invert the function. In particular, our result implies that if one can predict any of the bits of the input to a clas ...
Thermodynamic irreversibility can be imposed on empirical material behaviour by using an appropriate algorithm which takes the path-dependence of the degradation process into account. This new algorithm, Algorithmically Imposed Mechanics (AIM), for algorit ...
We present a novel class of decision diagrams, called Biconditional Binary Decision Diagrams (BBDDs), that enable efficient logic synthesis for XOR-rich functions. BBDDs are binary decision diagrams where the Shannon’s expansion is replaced by the bicondit ...
The knowledge of the thermal strain distribution of the Nb3Sn filaments in a cable in conduit conductor (CICC) cross section is a key parameter in understanding the cable performance evolution when it undergoes electromagnetic (EM) cyclic loading. A CICC i ...
This paper presents a cell-based approach for computing the deformation of a monitored object by analyzing point cloud data from terrestrial lidar. This approach can automatically generate an informative deformation description (called "deformation map") w ...
Multi-stage stochastic programming provides a versatile framework for optimal decision making under uncertainty, but it gives rise to hard functional optimization problems since the adaptive recourse decisions must be modeled as functions of some or all un ...
In this chapter an algorithm for nonlinear explicit model predictive control is presented. A low complexity receding horizon control law is obtained by approximating the optimal control law using multiscale basis function approximation. Simultaneously, fea ...
We discuss a model predictive control approach to trajectory tracking problems of constrained nonlinear con- tinuous time systems, where the reference trajectory is a priori known and asymptotically constant. The proposed NMPC scheme is able to explicitly ...