Real-Time and Low-Power Streaming Source Separation Using Markov Random Field

作者: Glenn G. Ko , Rob A. Rutenbar

DOI: 10.1145/3183351

关键词:

摘要: Machine learning (ML) has revolutionized a wide range of recognition tasks, ranging from text analysis to speech to vision, most notably in cloud deployments. However, mobile …

参考文章(45)
Harri Holma, Antti Toskala, LTE for UMTS: Evolution to LTE-Advanced ,(2011)
D. J. C. Mackay, Introduction to Monte Carlo methods Proceedings of the NATO Advanced Study Institute on Learning in graphical models. pp. 175- 204 ,(1998) , 10.1007/978-94-011-5014-9_7
C. Charoensak, F. Sattar, A single-chip FPGA design for real-time ICA-based blind source separation algorithm international symposium on circuits and systems. pp. 5822- 5825 ,(2005) , 10.1109/ISCAS.2005.1465962
Nir Friedman, Daniel L. Koller, Probabilistic graphical models : principles and techniques The MIT Press. ,(2009)
Erkki Oja, Aapo Hyvarinen, Juha Karhunen, Independent Component Analysis ,(2001)
Joshua B. Tenenbaum, Eric M. Jonas, Vikash K. Mansinghka, Stochastic Digital Circuits for Probabilistic Inference ,(2008)
Thomas E. Tkacik, A Hardware Random Number Generator cryptographic hardware and embedded systems. pp. 450- 453 ,(2002) , 10.1007/3-540-36400-5_32
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification international conference on computer vision. pp. 1026- 1034 ,(2015) , 10.1109/ICCV.2015.123
O. Yilmaz, S. Rickard, Blind separation of speech mixtures via time-frequency masking IEEE Transactions on Signal Processing. ,vol. 52, pp. 1830- 1847 ,(2004) , 10.1109/TSP.2004.828896
E. Colin Cherry, Some Experiments on the Recognition of Speech, with One and with Two Ears The Journal of the Acoustical Society of America. ,vol. 25, pp. 975- 979 ,(1953) , 10.1121/1.1907229