Browsing by Author "Chen, C. J."

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Device Instability of ReRAM and a Novel Reference Cell Design for Wide Temperature Range Operation
(2017-09-01)
Lin, Y. H.
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Lin, Y. Y.
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Lee, F. M.
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Ho, Y. H.
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Hsu, K. C.
This letter addresses two difficult challenges for transition metal oxide resistive random access memories (ReRAMs)-sensitivity to operation temperature and random fluctuation of resistance value. A careful study of a WOx ReRAM array reveals that these devices are unstable and their read currents fluctuate with time due to random telegraph noise and structure relaxation. Consequently, even after careful programming, the current distribution can broaden with time and tail bit population grows. Furthermore, ReRAM state is sensitive to temperature and a reference cell made of the same device material must be used. Thus, although the broadening of read current distribution may be tolerated by creating a larger RESET/SET memory window, the current fluctuation still makes it impossible to predict the output of the reference cell, leading to array malfunction. This letter investigates the current (resistance) instability in detail and proposes a reference array with a novel trimming method that can stabilize the reference current level. The proposed reference array has very good dc stress reliability as well as wide-range temperature tracking performance from -40 degrees C to 85 degrees C.
Perceptual Zero-Tree Coding with Efficient Optimization for Embedded Platforms
(2013-08-01)
Wu, B. F.
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Huang, H. Y.
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Wang, J. H.
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Chen, C. J.
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Chen, Y. L.
This study proposes a block-edge-based perceptual zero-tree coding (PZTC) method, which is implemented with efficient optimization on the embedded platform. PZTC combines two novel compression concepts for coding efficiency and quality: block-edge detection (BED) and the low-complexity and low-memory entropy coder (LLEC). The proposed PZTC was implemented as a fixed-point version and optimized on the DSP-based platform based on both the presented platform-independent and platform-dependent optimization technologies. For platform-dependent optimization, this study examines the fixed-point PZTC and analyzes the complexity to optimize PZTC toward achieving an optimal coding efficiency. Furthermore, hardware-based platform-dependent optimizations are presented to reduce the memory size. The performance, such as compression quality and efficiency, is validated by experimental results.