Search for dissertations about: "hidden Markov model HMM"
Showing result 1 - 5 of 23 swedish dissertations containing the words hidden Markov model HMM.
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1. Hidden Markov models : Identification, control and inverse filtering
Abstract : The hidden Markov model (HMM) is one of the workhorse tools in, for example, statistical signal processing and machine learning. It has found applications in a vast number of fields, ranging all the way from bioscience to speech recognition to modeling of user interactions in social networks. READ MORE
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2. Hidden Markov Models: Identification, Inverse Filtering and Applications
Abstract : A hidden Markov model (HMM) comprises a state with Markovian dynamics that is hidden in the sense that it can only be observed via a noisy sensor. This thesis considers three themes in relation to HMMs, namely, identification, inverse filtering and applications. READ MORE
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3. Face Recognition : A Single View Based HMM Approach
Abstract : This dissertation addresses the challenges of giving computers the ability of doing face recognition, i.e. discriminate between different faces. Face recognition systems are commonly trained with a database of face images, becoming “familiar” with the given faces. READ MORE
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4. Hidden Markov models - Traffic modeling and subspace methods
Abstract : The main motivation for this thesis, however not the only one, is the search for models for traffic in telecommunication networks. Traffic characterization and modeling are of great importance in the analysis and dimensioning of communication systems. During the last decades we have experienced an explosive growth of our telecommunication networks. READ MORE
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5. Model Based Speech Enhancement and Coding
Abstract : In mobile speech communication, adverse conditions, such as noisy acoustic environments and unreliable network connections, may severely degrade the intelligibility and natural- ness of the received speech quality, and increase the listening effort. This thesis focuses on countermeasures based on statistical signal processing techniques. READ MORE