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Showing papers in "IEEE Transactions on Circuits and Systems in 2021"


Journal ArticleDOI
TL;DR: Initial results for standard cell synthesis based on the authors' planar RFET device, featuring top-down planar silicon based technology, lower fabrication complexity than nanowire approaches and a high operating temperature robustness are presented.
Abstract: Reconfigurable FETs (RFETs) are ambipolar transistors featuring the ability to conduct both electrons and holes, which is often achieved through the use of silicon nanowires or similar gate-all-around topologies. In this article, we present initial results for standard cell synthesis based on our planar RFET device, featuring top-down planar silicon based technology, lower fabrication complexity than nanowire approaches and a high operating temperature robustness. We first introduce the device physics by explaining the structure and the operating principle on device level. We also summarize recent device optimizations to increase drive current and achieve symmetry between N- and P-type conduction. Next to CMOS-style standard cells, we present a reduced transistor count XOR cell and analyze timing. Transient simulations are performed entirely in TCAD to accurately show device performance. Further we describe extraction of relevant parameters of these circuits for usage in synthesis tools and compare our standard cells to a similar 180nmSOI technology. Afterwards we perform timing analysis for a full adder and explore the boundaries of our device with a larger cryptographic accelerator core.

10 citations


Journal ArticleDOI
TL;DR: In this paper, an iterative decimation approach is presented to reduce the computational burden of centralized controllers applying real-time recursive system identification algorithms in multi-rail power converters.
Abstract: This paper presents an iterative decimation approach to significantly alleviate the computational burden of centralized controllers applying real-time recursive system identification algorithms in multi-rail power converters. The proposed approach uses an adaptive update rate as opposed to the fixed update rate used in conventional adaptive filters. Also, the step size/forgetting factors vary at different iteration stages. As a result, a reduced computational burden and faster model update can be achieved. Besides, recursive algorithms, such as Recursive Least Square (RLS), Fast Affine Projection (FAP) and Kalman Filter (KF), contain two important updates per iteration cycle; Covariance Matrix Approximation (CMA) update and Gradient Vector (GV) update. Usually, the CMA update requires the greater computational effort than the GV update. Therefore, in circumstances where the sampled data in the regressor does not experience significant fluctuations, re-using the CMA, calculated from the last iteration cycle for the current update can result in computational cost savings for real-time system identification. In this paper, both iteration rate adjustment and CMA re-cycling are combined and applied to simultaneously identify the power converter models in a three-rail power conversion architecture.

2 citations