Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 165 for “"HMM"”.
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Discrete HMM isolated digit recognition
… word using discrete Hidden Markov Modeling (HMM) of the words. We discuss the discrete HMM in detail and explain why it is suitable for performing the recognition. A detailed explanation of the training algorithm used to train the HMM to recognize the words is presented. We evaluate the …
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Continuous HMM connected digit recognition
… and recognition, in a Hidden Markov Model (HMM) based speech recognition system. We use continuous mixture densities to approximate the observation probability density functions (pdfs) in the HMM. While more complex in implementation, continuous (observation) HMMs provide superior …
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Hmm-Based Semantic Learning for a Mobile Robot
… explores the use of hidden Markov models (HMMs) in this capacity. HMMs are capable of automatically learning and extracting the underlying structure of continuous-valued inputs and representing that structure in the states of the model. These states can then be treated as symbolic …
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An HMM-based boundary-flexible model of human haplotype variation
… haplotype boundaries. This thesis introduces an HMM-based boundary-flexible model, and proves that this model is superior to a blockwise description via the Minimum Description Length (MDL) criterion.
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Hardware acceleration of the pair HMM algorithm for DNA variant calling
Made available in DSpace on 2017-08-10T19:16:15Z (GMT). No. of bitstreams: 2 HUANG-THESIS-2017.pdf: 3198752 bytes, checksum: 355bc51ce749cb631e269cc6116f3c3f (MD5) LICENSE.txt: 4208 bytes, checksum: 29aa487d1a5b8c7beed523d9c3a35801 (MD5) Previous issue date: 2017-04-26
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Multicoil-HMM : improved prediction of coiled-coil oligomer state from sequence
The Multicoil-HMM algorithm offers improved prediction of coiled-coil oligomerization state. The algorithm combines the pairwise correlations of the Multicoil method with the flexibility of HMM methods. The resulting method incorporates predictors deemed important by a multinomial logistic …
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Improved GPU implementations of the Pair-HMM forward algorithm for DNA sequence alignment
The student, Enliang Li, accepted the attached license on 2021-04-30 at 13:30.
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Power Signal Analysis of Channel Current Signal Using HMM-EM and Time Domain FSA
… tools to analyze single molecule kinetics. The HMM-EM level projection method de-noises data, retaining the transitions with very high precision. This approach doesn't require input number of levels. Another advantage is the minimal tuning required. The levels are then identified using Finite …
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A comparative study of models for automatic speech recognition.
… Programming approach, the Hidden Markov Model (HMM), and the Neural Network, which are also evaluated by experiments. The reason why the HMM outperforms the other techniques is examined rigorously in the light of decision theory. The study firstly concludes that the success of the HMM approach …
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Autoregressive hidden Markov models and the speech signal
… an autoregressive hidden Markov model (HMM) and demonstrates its application to the speech signal. This new variant of the HMM is built upon the mathematical structure of the HMM and linear prediction analysis of speech signals. By incorporating these two methods into one inference …
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A novel reduced-complexity approach to hidden Markov modeling of two-dimensional processes with application to face recognition.
The 2-D Hidden Markov Model (HMM) is an extension of the traditional 1-D HMM that has shown distinctive efficiency in modeling 1-D signals. Unlike 1-D HMMs, 2-D HMMs are known for their prohibitively high complexity. This encouraged many researchers to work on alternatives such as Pseudo 2-D HMM …
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Generative Models for Retrieval of Video, Audio and Text Data
… is to first train a hidden Markov model (HMM) using the given example, it is called the theme HMM. The total audio data available is used to train a background HMM. We combine these individual HMMs to form a synthesized ""background-theme-background"" HMM. This synthesized HMM can then be …
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On improving the forecast accuracy of the hidden Markov model
The forecast accuracy of a hidden Markov model (HMM) may be low due first, to the measure of forecast accuracy being ignored in the parameterestimation method and, second, to overfitting caused by the large number of parameters that must be estimated. A general approach to forecasting is described …
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Path planning and control of flying robots with account of human’s safety perception
… reality environment. A hidden Markov model (HMM) is considered for estimation of latent variables, as user’s attention, intention, and emotional state. Then, an optimal motion planner generates a trajectory, parameterized in Bernstein polynomials, which minimizes the cost related to the …
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Meta State Generalized Hidden Markov Model for Eukaryotic Gene Structure Identification
Using a generalized-clique hidden Markov model (HMM) as the starting point for a eukaryotic gene finder, the objective here is to strengthen the signal information at the transitions between coding and non-coding (c/nc) regions. This is done by enlarging the primitive hidden states associated with …
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Enhancements in Markovian Dynamics
… linear generative model. Hidden Markov modeling (HMM), however, is categorized as an unsupervised learning under multiple linear/nonlinear generative models. This dissertation is primarily focused on hidden Markov models (HMMs). On the first half of this dissertation we study enhancements on the …
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A Translational Study Evaluating the Uses of Diagnostic and Therapeutic Practices Established in Human Malignant Melanoma in Equine Malignant Melanoma
… identified in both human malignant melanoma (HMM) and equine malignant melanoma (EMM). This work investigates similarities and differences of EMM and HMM through comparative protein expression using immunohistochemical staining. Nestin, Pax-3/7, B-Raf, and SOX-10 are commonly expressed in HMM …
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Bayesian nonparametric learning of complex dynamical phenomena
… The standard finite state hidden Markov model (HMM) has been widely applied in speech recognition, digital communications, and bioinformatics, amongst other fields. Through the use of the hierarchical Dirichlet process (HDP), one can examine an HMM with an unbounded number of possible states. We …
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Automatic Phoneme Recognition with Segmental Hidden Markov Models
… integrated elements. The Hidden Markov Model (HMM) based phoneme models are trained using the Baum-Welch re-estimation procedure. Recognition and segmentation of the phonemes in the continuous speech is performed by a Segmental Viterbi Search on a Segmental Ergodic HMM for the phoneme states. …
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Hidden Markov Models for analysis of pilot instrument scanning and attention switching
… budgeting among these tasks estimated by HMM analysis, combined with the pilots' eye-movement statistical results, could enhance a cockpit display format study. The experiments demonstrated what additional insights can be obtained by incorporating HMM analysis into the analysis of pilots' …
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