Zhigang Hao

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Basil, one of the most popular culinary herbs in North America is sold as a fresh-cut and dried processed product. There are over 40 cultivars available (De Baggio and Belsinger 1996), with many developed specifically for the fresh and/or ornamental markets. The popular cultivars for the fresh market and garden have dark green leaves and white flowers, with(More)
In this paper, we propose a new performance bound analysis of analog circuits considering process variations. We model the variations of component values as intervals measured from tested chip and manufacture processes. The new method applies a graph-based symbolic analysis and affine interval arithmetic to derive the variational transfer functions of(More)
Mesh circuits typically consist of many resistive links and many sources. Accurate analysis of massive mesh networks is demanding in the current integrated circuit design practice, yet their computation confronts numerous challenges. When variation is considered, mesh analysis becomes a much harder task. This paper proposes a symbolic computation technique(More)
— The shrinking technology feature size and dense large-scale integration make process variation a challenging issue directly confronting the latest design automation tools. Process variation causes severe variation in interconnect networks, including very large-scale integrated interconnect structures, such as clock trees, clock mesh, power-ground(More)
—In this paper, we propose a new time-domain performance bound analysis method for analog circuits considering process variations. The proposed method, called TIDBA, consists of several steps to compute the bound performances in time domain. First the performance bound in frequency domain is computed for a linearized analog circuits by an variational(More)
Estimation of battery state of charge (SOC) is essential for many emerging battery powered applications such as smart phones, electric and hybrid electric vehicles. In this paper, we propose a new battery SOC estimation method using adaptive subspace identification method. The subspace identification method is a numerically robust approach and is used to(More)
A reinforcement learning based I/O management is developed for energy-efficient communication between many-core microprocessor and memory. Instead of transmitting data under a fixed large voltage-swing, an online reinforcement Q-learning algorithm is developed to perform a self-adaptive voltage-swing control of 2.5D through-silicon interposer (TSI) I/O(More)