Memristive Circuits for LDPC Decoding
暂无分享,去创建一个
Jussi H. Poikonen | Mika Laiho | Jonne Poikonen | Eero Lehtonen | E. Lehtonen | M. Laiho | Jussi H. Poikonen | Jonne Poikonen
[1] Jussi H. Poikonen,et al. Large-Scale Memristive Associative Memories , 2014, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.
[2] William E. Ryan,et al. Quasi-Cyclic Generalized LDPC Codes With Low Error Floors , 2007, IEEE Trans. Commun..
[3] E. Lehtonen,et al. Arithmetic operations within memristor-based analog memory , 2010, 2010 12th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA 2010).
[4] Wei Yang Lu,et al. Nanoscale memristor device as synapse in neuromorphic systems. , 2010, Nano letters.
[5] David J. C. MacKay,et al. Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.
[6] L. Chua. Memristor-The missing circuit element , 1971 .
[7] R. Williams,et al. Nano/CMOS architectures using a field-programmable nanowire interconnect , 2007 .
[8] Xin-Yu Shih,et al. A real-time programmable LDPC decoder chip for arbitrary QC-LDPC parity check matrices , 2009, 2009 IEEE Asian Solid-State Circuits Conference.
[9] Leon O. Chua. Resistance switching memories are memristors , 2011 .
[10] Shu Lin,et al. Low-density parity-check codes based on finite geometries: A rediscovery and new results , 2001, IEEE Trans. Inf. Theory.
[11] Joachim Neves Rodrigues,et al. Ultra-Low-Power Error Correction Circuits: Technology Scaling and Sub-$V_{ \rm T}$ Operation , 2012, IEEE Transactions on Circuits and Systems II: Express Briefs.
[12] Andreas Mayr,et al. CrossNets: High‐Performance Neuromorphic Architectures for CMOL Circuits , 2003, Annals of the New York Academy of Sciences.
[13] Karthik Ganesan,et al. Choosing “green” codes by simulation-based modeling of implementations , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).
[14] Jussi H. Poikonen,et al. On Synthesis of Boolean Expressions for Memristive Devices Using Sequential Implication Logic , 2012, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.
[15] J. Poikonen,et al. Erratum for Two memristors suffice to compute all Boolean functions , 2010 .
[16] Ligang Gao,et al. High precision tuning of state for memristive devices by adaptable variation-tolerant algorithm , 2011, Nanotechnology.
[17] Benjamin Peter Smith,et al. Error-correcting Codes for Fibre-optic Communication Systems , 2012 .
[18] Xiaohu You,et al. New insights into weighted bit-flipping decoding , 2009, IEEE Transactions on Communications.
[19] Uri C. Weiser,et al. Memristor-Based Material Implication (IMPLY) Logic: Design Principles and Methodologies , 2014, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.
[20] Dmitri B Strukov,et al. Four-dimensional address topology for circuits with stacked multilayer crossbar arrays , 2009, Proceedings of the National Academy of Sciences.
[21] Jussi H. Poikonen,et al. Memristive Stateful Logic , 2014 .
[22] D. Strukov,et al. CMOL: Devices, Circuits, and Architectures , 2006 .
[23] Jussi H. Poikonen,et al. A cellular computing architecture for parallel memristive stateful logic , 2014, Microelectron. J..
[24] Siddharth Gaba,et al. Nanoscale resistive memory with intrinsic diode characteristics and long endurance , 2010 .
[25] Kinam Kim,et al. A fast, high-endurance and scalable non-volatile memory device made from asymmetric Ta2O(5-x)/TaO(2-x) bilayer structures. , 2011, Nature materials.
[26] Narayan Srinivasa,et al. A functional hybrid memristor crossbar-array/CMOS system for data storage and neuromorphic applications. , 2012, Nano letters.
[27] W. Lu,et al. Programmable Resistance Switching in Nanoscale Two-terminal Devices , 2008 .
[28] G. Snider,et al. Self-organized computation with unreliable, memristive nanodevices , 2007 .
[29] Wonyong Sung,et al. VLSI Implementation of a High-Throughput Soft-Bit-Flipping Decoder for Geometric LDPC Codes , 2010, IEEE Transactions on Circuits and Systems I: Regular Papers.
[30] Robert G. Gallager,et al. The random coding bound is tight for the average code (Corresp.) , 1973, IEEE Trans. Inf. Theory.