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A low-computation-complexity, energy-efficient, and high-performance linear program solver using memristor crossbars., , , , , , и . SoCC, стр. 317-322. IEEE, (2016)Memristor crossbar-based ultra-efficient next-generation baseband processors., , , , , , , и . MWSCAS, стр. 1121-1124. IEEE, (2017)A low-computation-complexity, energy-efficient, and high-performance linear program solver based on primal-dual interior point method using memristor crossbars., , , и . Nano Commun. Networks, (2018)Algorithm-Hardware Co-Optimization of the Memristor-Based Framework for Solving SOCP and Homogeneous QCQP Problems., , , , , и . CoRR, (2018)IDE Development, Logic Synthesis and Buffer/Splitter Insertion Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits., , , , , , и . ISVLSI, стр. 187-192. IEEE, (2019)Hardware Acceleration of Bayesian Neural Networks Using RAM Based Linear Feedback Gaussian Random Number Generators., , , , и . ICCD, стр. 289-296. IEEE Computer Society, (2017)A Buffer and Splitter Insertion Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits., , , , , и . ICCD, стр. 429-436. IEEE, (2019)A Majority Logic Synthesis Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits., , , , , , и . ACM Great Lakes Symposium on VLSI, стр. 189-194. ACM, (2019)Algorithm-hardware co-optimization of the memristor-based framework for solving SOCP and homogeneous QCQP problems., , , , , и . ASP-DAC, стр. 788-793. IEEE, (2017)A stochastic-computing based deep learning framework using adiabatic quantum-flux-parametron superconducting technology., , , , , , , , , и . ISCA, стр. 567-578. ACM, (2019)