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Linear models are regularly used for mapping cores to tiles in a chip. System-on-Chip (SoC) design requires integration of functional units with varying sizes, but conventional models only account for identical-sized cores. Linear models cannot calculate the varying areas of cores in SoCs directly and must rely on approximations. We propose using non-linear models: Semi-definite programming (SDP) allows easy model definitions and achieves approximately 20% reduced area and up to 80% reduced white space. As computational time is similar to linear models, they can be applied, practically.
For a system-level design of Networks-on-Chip for 3D heterogeneous System-on-Chip (SoC), the locations of components, routers and vertical links are determined from an application model and technology parameters. In conventional methods, the two inpu
We propose a new system identification method, called Sign-Perturbed Sums (SPS), for constructing non-asymptotic confidence regions under mild statistical assumptions. SPS is introduced for linear regression models, including but not limited to FIR s
Leaf area index (LAI) is a key biophysical parameter used to determine foliage cover and crop growth in environmental studies. Smartphones are nowadays ubiquitous sensor devices with high computational power, moderate cost, and high-quality sensors.
This letter investigates the uplink of a multi-user millimeter wave (mmWave) system, where the base station (BS) is equipped with a massive multiple-input multiple-output (MIMO) array and resolution-adaptive analog-to-digital converters (RADCs). Alth
We propose a three-track detection system for two dimensional magnetic recording (TDMR) in which a local area influence probabilistic (LAIP) detector works with a trellis-based Bahl-Cocke-Jelinek-Raviv (BCJR) detector to remove intersymbol interferen