FPGA implementation of logarithmic versions of Baum-Welch and Viterbi algorithms for reduced precision hidden Markov models

Journal title

Bulletin of the Polish Academy of Sciences: Technical Sciences




No 6

Publication authors

Divisions of PAS

Nauki Techniczne


Polish Academy of Sciences




ISSN 0239-7528, eISSN 2300-1917


Choi (2010), real time FPGA based word speech recognizer with optimized DRAM access, IEEE Trans Circuits Syst Reg Papers, 12, 000. ; Yu (2014), Accelerated HMM for speech recognition rd International Conference on Parallel Processing Workshops Minneapolis, null, 395, ; Dhawan (null), Area - efficient near - associative memories on ACM Transactions on Reconfigurable Technology and Systems, null, 29, 2015, ; Chrysos (2012), Opportunities from the use of FPGAs as platforms for bioinformatics algorithms International Conference on, Bioinformatics, 17, 559, ; Panuccio (2002), hidden Markov model - based approach to sequential data clustering Structural Syntactic and, Statistical Pattern Recognition, 734, ; Brown (2009), tutorial of techniques for improving standard hidden Markov model algorithms Computational Biology, Bioinformatics, 16, 737, ; Jun Li (2009), The fast evaluation of hidden Markov models on GPU International Conference on Intelligent Computing and Intelligent Systems Shanghai, IEEE, 31, 426, ; Pietras (2016), Hidden Markov models with affix based observation in the field of syntactic analysis In for eds, Soft Computing Artificial Intelligence Multimedia Security, 534, ; Singh (2014), Dynamic classification of ballistic missiles using neural networks and hidden Markov models, Applied Soft Computing, 19, 280. ; Churbanov (2008), Implementing EM and Viterbi algorithms for hidden Markov model in linear memory, BMC Bioinformatics, 22, 1, ; Varma (2010), Easing the verification bottleneck using high level synthesis th Test Santa, VLSI Symposium, 24, 253, ; Anisha (null), hybrid Parts Of Speech tagger for Malayalam language International Conference on Advances in Communications and, Computing, 26, 1502, ; Hsieh (2014), An HMM - based eye movement detection system using EEG brain - computer interface International Symposium on Circuits and Systems Melbourne VIC, IEEE, 13, 662, ; Behnam (1509), Stats - calculus pose descriptor feeding a discrete HMM low - latency detection and recognition system for skeletal actions arXiv preprint arXiv, null, 09014. ; Rabiner (1989), tutorial on hidden Markov models and selected applications in speech recognition of the, Proceedings IEEE, 15, 77, ; Narasimhan (2006), Online decoding of Markov models under latency constraints in pp, null, 657, ; Taehwan (2011), HMM - based underwater target classification with synthesized active sonar signals, Trans, 9, 2039, ; Atef (2016), Reconfigurable hardware accelerator for profile hidden Markov models for and, Arabian Journal Science Engineering, 18, 3267. ; Majumder (2014), Hardware accelerators in computational biology application potential challenges Test, IEEE Design, 21, 8, ; Mannini (2014), Online decoding of hidden Markov models for gait event detection using foot - mounted gyroscopes of, IEEE Journal Health, 18, 1122, ; Sun (2009), Accelerating HMMer on FPGAs using systolic array based architecture Proceedings of the rd International and Distributed Processing, IEEE Parallel Symposium, 20, ; Vinyals (2008), Hardware - independent fast logarithm approximation with adjustable accuracy International on, IEEE Symposium Multimedia, 28, 61, ; Manandhar (null), Multiple - instance hidden Markov model for gpr - based landmine detection on and, IEEE Transactions Geoscience Remote Sensing, 53, 1737. ; Loughlin (2014), vivado high level synthesis case studies Signals and Systems Conference Limerick, null, 25, 352, ; Lyu (null), vision based sense and avoid system for small unmanned helicopter International Conference on Unmanned Aircraft Systems Denver, null, 14, 2015, ; Knuth (1998), The art of computer programming Section Sorting by Merging Sorting and Searching nd ed, null, 30, 158. ; Vargas (2001), based Viterbi algorithm implementation for speech recognition systems International Conference on Acoustics and Processing, IEEE Speech Signal ICASSP, 19, 01, ; Mann (2006), Numerically stable hidden Markov model implementation HMM scaling tutorial, null, 27, 1. ; Shannon (2013), Zen Autoregressive models for statistical parametric speech synthesis Process, Trans Audio Speech Language, 21, 587, ; Tatavarty (2011), Implementation of numerically stable hidden Markov model UNLV Theses Dissertations Professional Paper, Papers, 23, 1018. ; Mari (2005), Temporal and spatial data mining with second - order hidden Markov models, Soft Computing, 10, 1, ; Kubanek (2012), Characteristics of the use of coupled hidden Markov models for audio - visual Polish speech recognition Pol, Tech, 307, ; Bapat (2013), Acoustic coprocessor for hmm based embedded speech recognition systems on, IEEE Transactions Consumer Electronics, 11, 59,