منابع مشابه
Reduced space hidden Markov model training
MOTIVATION Complete forward-backward (Baum-Welch) hidden Markov model training cannot take advantage of the linear space, divide-and-conquer sequence alignment algorithms because of the examination of all possible paths rather than the single best path. RESULTS This paper discusses the implementation and performance of checkpoint-based reduced space sequence alignment in the SAM hidden Markov...
متن کاملReduced Space Hidden Markov Model Training
1 Abstract 1.1 Motivation Complete forward-backward (Baum-Welch) hidden Markov model training cannot take advantage of the linear space, divide-and-conquer sequence alignment algorithms because of the examination of all possible paths rather than the single best path. This paper discusses the implementation and performance of checkpoint-based reduced space sequence alignment in the SAM Hidden M...
متن کاملReduced space hidden Markov model
1 Abstract 1.1 Motivation Complete forward-backward (Baum-Welch) hidden Markov model training cannot take advantage of the linear space, divide-and-conquer sequence alignment algorithms because of the examination of all possible paths rather than the single best path. This paper discusses the implementation and performance of checkpoint-based reduced space sequence alignment in the SAM Hidden M...
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Intrusion detection systems are responsible for diagnosing and detecting any unauthorized use of the system, exploitation or destruction, which is able to prevent cyber-attacks using the network package analysis. one of the major challenges in the use of these tools is lack of educational patterns of attacks on the part of the engine analysis; engine failure that caused the complete training, ...
متن کاملReduced-Rank Hidden Markov Models
We introduce the Reduced-Rank Hidden Markov Model (RR-HMM), a generalization of HMMs that can model smooth state evolution as in Linear Dynamical Systems (LDSs) as well as non-log-concave predictive distributions as in continuous-observation HMMs. RR-HMMs assume anm-dimensional latent state and n discrete observations, with a transition matrix of rank k ≤ m. This implies the dynamics evolve in ...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 1998
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/14.5.401