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An ARPES study of correlated electron materials on the verge of cooperative orderTrinckauf, Jan 30 June 2014 (has links)
In this thesis the charge dynamics of correlated electron systems, in which a metallic phase lies in close proximity to an ordered phase, are investigated by means of angle resolved photoemission spectroscopy (ARPES). The analysis of the experimental data is complemented by electronic structure calculations within the framework of density functional theory (DFT).
First the charge dynamics of the colossal magnetoresistant bilayer manganites are studied. The analysis of the ARPES spectra based on DFT calculations and a Peierls type charge density wave model, suggests that charge, orbital, spin and lattice degrees of freedom conspire to form a fluctuating two dimensional local order that produces a large pseudo gap of about 450 meV in the ferromagnetic metallic phase and that reduces the expected bilayer splitting.
Next, the interplay of Kondo physics and (magnetic) order in the heavy fermion superconductor URu2Si2 is investigated. The low energy electronic structure undergoes strong changes at 17.5 K, where a second order phase transition occurs whose phenomenology is well characterized, but whose order parameter could not yet be unambigeously identified. Below THO, non-dispersive quasi particles with a large scattering rate suddenly acquire dispersion and start to hybridize with the conduction band electrons. Simultaniously the scattering rate drops sinificantly and a large portion of the Fermi surface vanishes due to the opening of a gap within the band of heavy quasi particles. The observed behaviour is in stark contrast to conventional heavy fermion systems where the onset of hybridization between localized and itinerant carriers happens in a crossover type transition rather than abruptly. These experimental results suggest that Kondo screening and the hidden order parameter work together to produce the unusual thermodynamic signatures observed in this compound.
Finally, the influence of charge doping and impurity scattering on the superconducting porperties of the transition metal substituted iron pnictide superconductor Ba(Fe1-xTMx)2As2 (TM = Co, Ni) is studied. Here, resonant soft X-ray ARPES is applied to see element selective the contribution of the 3d states of the TM substitute to the Fe 3d host bands.
The spectroscopic signatures of the substitution are found to be well reproduced by DFT supercell and model impurity calculations. Namely, the hybridization of the dopant with the host decreases with increasing impurity potential and the electronic states of the impurtiy become increasingly localized. Simultaniously, in all simulated cases a shift of the Fermi level due to electron doping is observed. The magnitude of the shift in the chemical potential that accurs in BaFe2As2, however, is in stark contrast to the marginal doping values obtained for the impurity model, where the shift of the chemical potential is largely compensated by the influence of the increasing impurity potential. This suggests that the rigid band behaviour of TM substituded BaFe2As2 is a peculiarity of the compound, which has strong implications for the developement of superconductivity. / In dieser Arbeit wird die Ladungstraegerdynamik in korrelierten Elektronensystemen, in denen eine metallische Phase in direkter Nachbarschaft zu einer geordneten Phase liegt, mit Hilfe von winkelaufgeloester Photoelektronenspektroskopie (ARPES) untersucht. Die Analyse der experimentellen Daten wird ergaenzt durch lektronenstrukturrechnungen im Rahmen der Dichtefunktionaltheorie (DFT).
Zuerst wird die Ladungstraegerdynamik in gemischtvalenten zweischichtmanganaten mit kolossalem Magnetiwiderstand studiert. Die Analyse der Photoemissionsspektren basierend auf DFT Rechnungen und einem Peierls artigem Ladungsdichtewellenmodell, legt nahe, dass die Freiheitsgrade von Ladung, Orbitalen, Spin und des Ionengitters konspirieren, um eine fluktuierende zweidimensionale lokale Ordnung zu bilden, die verantwortlich ist fuer die beobachtete Pseudobandluecke von 450 meV, und die zur Reduktion der erwarteten Zweischichtaufspaltung beitraegt. Als naechstes wird das Zusammenspiel von Kondo Physik und (magnetischer) Ordung im Schwerfermionensupraleiter URu2Si2 untersucht. Die iedrigenergetische elektronische Struktur zeigt starke Veraenderungen bei 17.5 K, wo ein Phasenuebergang zweiter Ordnungstattfindet, der phenomenologisch gut charakterisiert ist, aber dessen Ordungsparameter nocht nicht eindeutig identifiziert werden konnte. Unterhalb von THOerlangen nicht dispergierende Quasiteilchen mit gro en Streuraten abrupt Dispersion und hybridisieren mit den Leitungselektronen. Gleichzeitig sinkt die Streurate und ein gro er Teil der Fermiflaeche verschwindet durch das Oeffnen einer Bandluecke innehalb des Bandes schwerer Quasiteilchen.
Das beobachtete Verhalten steht in starkem Kontrast zu dem von konventionellen Schwerfermionensystemen, in denen die Hybridisierung zwischen lokalisierten und itineranten Ladungstraegern in einem kontinuierlichen Uebergang ablaeuft, anstatt abrubt. Diese experimentellen Befunde lassen den Schluss zu, dass das zusammenspiel zwischen Kondo Abschirmung und dem unbekannten Ordnungsparameter die ungewoehnlichen thermodynamischen Signaturen in dieser Verbindung hervorruft.
Abschliessend wird das Zusammenwirken von Ladungstraegerdotierung und Streuung an Stoeratomen auf die Supraleitung uebergangsmetalldotierter Eisenpniktid Supraleiter Ba(Fe1-xTMx)2As2 (TM = Co, Ni) untersucht. Mit Hilfe von resonantem Weichenroentgen ARPES gelingt es, elementselektiv den Beitrag der 3d Zustaende des TM Substituenten zu den Eisen 3d Wirtsbaendern zu beobachten. Die spektroskopischen Signaturen der Substitution sind mit Hilfe von DFT Rechnungen und Modelrechnungen mit zufaellig verteilten Stoeratomen gut zu reproduzieren. Insbesondere nimmt die Hybridisierung des dotierten Uebergangsmetalls und der Eisenbaender mit zunehmender Kernladungszahl ab und die elektronischen Zustaende der Stoeratome werden zunehmen lokalisiert. Gleichzeitig wird in allen gerechneten Faellen eine Verschiebung des Fermi Niveaus durch Elektronendotierung beobachtet. Der Betrag der Verschiebung des chemischen Potentials in BaFe2As2 steht allerdings in starkem Kontrast zu den Werten, die man im Falle der Modellrechnungen erhaelt, wo die Verschiebung des Fermi Niveaus durch den Einfluss des Potentials der Stoeratome groesstenteils kompensiert wird. Dies legt nahe, dass das beobachtete "rigid band" Verhalten von TM substituiertem BaFe2As2 eine Besonderheit dieser Verbindung ist, welches starke Auswirkungen auf die Ausbildung von Supraleitung hat.
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Training of Hidden Markov models as an instance of the expectation maximization algorithmMajewsky, Stefan 22 August 2017 (has links)
In Natural Language Processing (NLP), speech and text are parsed and generated with language models and parser models, and translated with translation models. Each model contains a set of numerical parameters which are found by applying a suitable training algorithm to a set of training data.
Many such training algorithms are instances of the Expectation-Maximization (EM) algorithm. In [BSV15], a generic EM algorithm for NLP is described. This work presents a particular speech model, the Hidden Markov model, and its standard training algorithm, the Baum-Welch algorithm. It is then shown that the Baum-Welch algorithm is an instance of the generic EM algorithm introduced by [BSV15], from which follows that all statements about the generic EM algorithm also apply to the Baum-Welch algorithm, especially its correctness and convergence properties.:1 Introduction
1.1 N-gram models
1.2 Hidden Markov model
2 Expectation-maximization algorithms
2.1 Preliminaries
2.2 Algorithmic skeleton
2.3 Corpus-based step mapping
2.4 Simple counting step mapping
2.5 Regular tree grammars
2.6 Inside-outside step mapping
2.7 Review
3 The Hidden Markov model
3.1 Forward and backward algorithms
3.2 The Baum-Welch algorithm
3.3 Deriving the Baum-Welch algorithm
3.3.1 Model parameter and countable events
3.3.2 Tree-shaped hidden information
3.3.3 Complete-data corpus
3.3.4 Inside weights
3.3.5 Outside weights
3.3.6 Complete-data corpus (cont.)
3.3.7 Step mapping
3.4 Review
Appendix
A Elided proofs from Chapter 3
A.1 Proof of Lemma 3.8
A.2 Proof of Lemma 3.9
B Formulary for Chapter 3
Bibliography
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Frequency based efficiency evaluation - from pattern recognition via backwards simulation to purposeful drive designStarke, Martin, Beck, Benjamin, Ritz, Denis, Will, Frank, Weber, Jürgen 23 June 2020 (has links)
The efficiency of hydraulic drive systems in mobile machines is influenced by several factors, like the operators’ guidance, weather conditions, material respectively loading properties and primarily the working cycle. This leads to varying operation points, which have to be performed by the drive system. Regarding efficiency analysis, the usage of standardized working cycles gained through measurements or synthetically generated is state of the art. Thereby, only a small extract of the real usage profile is taken into account. This contribution deals with process pattern recognition (PPR) and frequency based efficiency evaluation to gain more precise information and conclusion for the drive design of mobile machines. By the example of an 18 t mobile excavator, the recognition system using Hidden – Markov - Models (HMM) and the efficiency evaluation process by means of backwards simulation of measured operation points will be described.
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Models of Discrete-Time Stochastic Processes and Associated Complexity MeasuresLöhr, Wolfgang 12 May 2010 (has links)
Many complexity measures are defined as the size of a minimal representation in
a specific model class. One such complexity measure, which is important because
it is widely applied, is statistical complexity. It is defined for
discrete-time, stationary stochastic processes within a theory called
computational mechanics. Here, a mathematically rigorous, more general version
of this theory is presented, and abstract properties of statistical complexity
as a function on the space of processes are investigated. In particular, weak-*
lower semi-continuity and concavity are shown, and it is argued that these
properties should be shared by all sensible complexity measures. Furthermore, a
formula for the ergodic decomposition is obtained.
The same results are also proven for two other complexity measures that are
defined by different model classes, namely process dimension and generative
complexity. These two quantities, and also the information theoretic complexity
measure called excess entropy, are related to statistical complexity, and this
relation is discussed here.
It is also shown that computational mechanics can be reformulated in terms of
Frank Knight''s prediction process, which is of both conceptual and technical
interest. In particular, it allows for a unified treatment of different
processes and facilitates topological considerations. Continuity of the Markov
transition kernel of a discrete version of the prediction process is obtained as
a new result.
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A Multi-Target Graph-Constrained HMM Localisation Approach using Sparse Wi-Fi Sensor Data / Graf-baserad HMM Lokalisering med Wi-Fi Sensordata av GångtrafikanterDanielsson, Simon, Flygare, Jakob January 2018 (has links)
This thesis explored the possibilities of using a Hidden Markov Model approach for multi-target localisation in an urban environment, with observations generated from Wi-Fi sensors. The area is modelled as a network of nodes and arcs, where the arcs represent sidewalks in the area and constitutes the hidden states in the model. The output of the model is the expected amount of people at each road segment throughout the day. In addition to this, two methods for analyzing the impact of events in the area are proposed. The first method is based on a time series analysis, and the second one is based on the updated transition matrix using the Baum-Welch algorithm. Both methods reveal which road segments are most heavily affected by a surge of traffic in the area, as well as potential bottleneck areas where congestion is likely to have occurred. / I det här examensarbetet har lokalisering av gångtrafikanter med hjälp av Hidden Markov Models utförts. Lokaliseringen är byggd på data från Wi-Fi sensorer i ett område i Stockholm. Området är modellerat som ett graf-baserat nätverk där linjerna mellan noderna representerar möjliga vägar för en person att befinna sig på. Resultatet för varje individ är aggregerat för att visa förväntat antal personer på varje segment över en hel dag. Två metoder för att analysera hur event påverkar området introduceras och beskrivs. Den första är baserad på tidsserieanalys och den andra är en maskinlärningsmetod som bygger på Baum-Welch algoritmen. Båda metoderna visar vilka segment som drabbas mest av en snabb ökning av trafik i området och var trängsel är troligt att förekomma.
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Off-line signature verification using ensembles of local Radon transform-based HMMsPanton, Mark Stuart 03 1900 (has links)
Thesis (MSc)--Stellenbosch University, 2011. / ENGLISH ABSTRACT: An off-line signature verification system attempts to authenticate the identity
of an individual by examining his/her handwritten signature, after it has
been successfully extracted from, for example, a cheque, a debit or credit card
transaction slip, or any other legal document. The questioned signature is typically
compared to a model trained from known positive samples, after which
the system attempts to label said signature as genuine or fraudulent.
Classifier fusion is the process of combining individual classifiers, in order to
construct a single classifier that is more accurate, albeit computationally more
complex, than its constituent parts. A combined classifier therefore consists
of an ensemble of base classifiers that are combined using a specific fusion
strategy.
In this dissertation a novel off-line signature verification system, using a
multi-hypothesis approach and classifier fusion, is proposed. Each base classifier
is constructed from a hidden Markov model (HMM) that is trained from
features extracted from local regions of the signature (local features), as well as
from the signature as a whole (global features). To achieve this, each signature
is zoned into a number of overlapping circular retinas, from which said features
are extracted by implementing the discrete Radon transform. A global retina,
that encompasses the entire signature, is also considered.
Since the proposed system attempts to detect high-quality (skilled) forgeries,
it is unreasonable to assume that samples of these forgeries will be available
for each new writer (client) enrolled into the system. The system is therefore
constrained in the sense that only positive training samples, obtained
from each writer during enrolment, are available. It is however reasonable to
assume that both positive and negative samples are available for a representative
subset of so-called guinea-pig writers (for example, bank employees). These signatures constitute a convenient optimisation set that is used to select
the most proficient ensemble. A signature, that is claimed to belong to
a legitimate client (member of the general public), is therefore rejected or accepted
based on the majority vote decision of the base classifiers within the
most proficient ensemble.
When evaluated on a data set containing high-quality imitations, the inclusion
of local features, together with classifier combination, significantly increases
system performance. An equal error rate of 8.6% is achieved, which
compares favorably to an achieved equal error rate of 12.9% (an improvement
of 33.3%) when only global features are considered.
Since there is no standard international off-line signature verification data
set available, most systems proposed in the literature are evaluated on data
sets that differ from the one employed in this dissertation. A direct comparison
of results is therefore not possible. However, since the proposed system
utilises significantly different features and/or modelling techniques than those
employed in the above-mentioned systems, it is very likely that a superior combined
system can be obtained by combining the proposed system with any of
the aforementioned systems. Furthermore, when evaluated on the same data
set, the proposed system is shown to be significantly superior to three other
systems recently proposed in the literature. / AFRIKAANSE OPSOMMING: Die doel van ’n statiese handtekening-verifikasiestelsel is om die identiteit
van ’n individu te bekragtig deur sy/haar handgeskrewe handtekening te analiseer,
nadat dit suksesvol vanaf byvoorbeeld ’n tjek,’n debiet- of kredietkaattransaksiestrokie,
of enige ander wettige dokument onttrek is. Die bevraagtekende
handtekening word tipies vergelyk met ’n model wat afgerig is met bekende
positiewe voorbeelde, waarna die stelsel poog om die handtekening as eg
of vervals te klassifiseer.
Klassifiseerder-fusie is die proses waardeer individuele klassifiseerders gekombineer
word, ten einde ’n enkele klassifiseerder te konstrueer, wat meer akkuraat,
maar meer berekeningsintensief as sy samestellende dele is. ’n Gekombineerde
klassifiseerder bestaan derhalwe uit ’n ensemble van basis-klassifiseerders,
wat gekombineer word met behulp van ’n spesifieke fusie-strategie.
In hierdie projek word ’n nuwe statiese handtekening-verifikasiestelsel, wat
van ’n multi-hipotese benadering en klassifiseerder-fusie gebruik maak, voorgestel.
Elke basis-klassifiseerder word vanuit ’n verskuilde Markov-model (HMM)
gekonstrueer, wat afgerig word met kenmerke wat vanuit lokale gebiede in die
handtekening (lokale kenmerke), sowel as vanuit die handtekening in geheel
(globale kenmerke), onttrek is. Ten einde dit te bewerkstellig, word elke
handtekening in ’n aantal oorvleulende sirkulêre retinas gesoneer, waaruit kenmerke
onttrek word deur die diskrete Radon-transform te implementeer. ’n
Globale retina, wat die hele handtekening in beslag neem, word ook beskou.
Aangesien die voorgestelde stelsel poog om hoë-kwaliteit vervalsings op te
spoor, is dit onredelik om te verwag dat voorbeelde van hierdie handtekeninge
beskikbaar sal wees vir elke nuwe skrywer (kliënt) wat vir die stelsel registreer.
Die stelsel is derhalwe beperk in die sin dat slegs positiewe afrigvoorbeelde, wat
bekom is van elke skrywer tydens registrasie, beskikbaar is. Dit is egter redelik om aan te neem dat beide positiewe en negatiewe voorbeelde beskikbaar sal
wees vir ’n verteenwoordigende subversameling van sogenaamde proefkonynskrywers,
byvoorbeeld bankpersoneel. Hierdie handtekeninge verteenwoordig
’n gereieflike optimeringstel, wat gebruik kan word om die mees bekwame ensemble
te selekteer. ’n Handtekening, wat na bewering aan ’n wettige kliënt
(lid van die algemene publiek) behoort, word dus verwerp of aanvaar op grond
van die meerderheidstem-besluit van die basis-klassifiseerders in die mees bekwame
ensemble.
Wanneer die voorgestelde stelsel op ’n datastel, wat hoë-kwaliteit vervalsings
bevat, ge-evalueer word, verhoog die insluiting van lokale kenmerke en
klassifiseerder-fusie die prestasie van die stelsel beduidend. ’n Gelyke foutkoers
van 8.6% word behaal, wat gunstig vergelyk met ’n gelyke foutkoers van 12.9%
(’n verbetering van 33.3%) wanneer slegs globale kenmerke gebruik word.
Aangesien daar geen standard internasionale statiese handtekening-verifikasiestelsel
bestaan nie, word die meeste stelsels, wat in die literatuur voorgestel
word, op ander datastelle ge-evalueer as die datastel wat in dié projek gebruik
word. ’n Direkte vergelyking van resultate is dus nie moontlik nie. Desnieteenstaande,
aangesien die voorgestelde stelsel beduidend ander kenmerke
en/of modeleringstegnieke as dié wat in bogenoemde stelsels ingespan word gebruik,
is dit hoogs waarskynlik dat ’n superieure gekombineerde stelsel verkry
kan word deur die voorgestelde stelsel met enige van bogenoemde stelsels te
kombineer. Voorts word aangetoon dat, wanneer op dieselfde datastel geevalueerword,
die voorgestelde stelstel beduidend beter vaar as drie ander
stelsels wat onlangs in die literatuur voorgestel is.
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Caractérisation des images à Rayon-X de la main par des modèles mathématiques : application à la biométrie / « Characterization of X-ray images of the hand by mathematical models : application to biometrics »Kabbara, Yeihya 09 March 2015 (has links)
Dans son contexte spécifique, le terme « biométrie » est souvent associé à l'étude des caractéristiques physiques et comportementales des individus afin de parvenir à leur identification ou à leur vérification. Ainsi, le travail développé dans cette thèse nous a conduit à proposer un algorithme d'identification robuste, en considérant les caractéristiques intrinsèques des phalanges de la main. Considérée comme une biométrie cachée, cette nouvelle approche peut s'avérer intéressante, notamment lorsqu'il est question d'assurer un niveau de sécurité élevé, robuste aux différentes attaques qu'un système biométrique doit contrer. La base des techniques proposées requière trois phases, à savoir: (1) la segmentation des phalanges, (2) l'extraction de leurs caractéristiques par la génération d'une empreinte, appelée « Phalange-Code » et (3) l'identification basée sur la méthode du 1-plus proche voisin ou la vérification basée sur une métrique de similarité. Ces algorithmes opèrent sur des niveaux hiérarchiques permettant l'extraction de certains paramètres, invariants à des transformations géométriques telles que l'orientation et la translation. De plus, nous avons considéré des techniques robustes au bruit, pouvant opérer à différentes résolutions d'images. Plus précisément, nous avons élaboré trois approches de reconnaissance biométrique : la première approche utilise l'information spectrale des contours des phalanges de la main comme signature individuelle, alors que la deuxième approche nécessite l'utilisation des caractéristiques géométriques et morphologiques des phalanges (i.e. surface, périmètre, longueur, largeur, capacité). Enfin, la troisième approche requière la génération d'un nouveau rapport de vraisemblance entre les phalanges, utilisant la théorie de probabilités géométriques. En second lieu, la construction d'une base de données avec la plus faible dose de rayonnement a été l'un des grands défis de notre étude. Nous avons donc procédé par la collecte de 403 images radiographiques de la main, acquises en utilisant la machine Apollo EZ X-Ray. Ces images sont issues de 115 adultes volontaires (hommes et femmes), non pathologiques. L'âge moyen étant de 27.2 ans et l'écart-type est de 8.5. La base de données ainsi construite intègre des images de la main droite et gauche, acquises à des positions différentes et en considérant des résolutions différentes et des doses de rayonnement différentes (i.e. réduction jusqu'à 98 % de la dose standard recommandée par les radiologues « 1 µSv »).Nos expériences montrent que les individus peuvent être distingués par les caractéristiques de leurs phalanges, que ce soit celles de la main droite ou celles de la main gauche. Cette distinction est également valable pour le genre des individus (homme/femme). L'étude menée a montré que l'approche utilisant l'information spectrale des contours des phalanges permet une identification par seulement trois phalanges, à un taux EER (Equal Error Rate) inférieur à 0.24 %. Par ailleurs, il a été constaté « de manière surprenante » que la technique fondée sur les rapports de vraisemblance entre les phalanges permet d'atteindre un taux d'identification de 100 % et un taux d'EER de 0.37 %, avec une seule phalange. Hormis l'aspect identification/authentification, notre étude s'est penchée sur l'optimisation de la dose de rayonnement permettant une identification saine des individus. Ainsi, il a été démontré qu'il était possible d'acquérir plus de 12500/an d'images radiographiques de la main, sans pour autant dépasser le seuil administratif de 0.25 mSv / In its specific context, the term "biometrics" is often associated with the study of the physical and behavioral of individual's characteristics to achieve their identification or verification. Thus, the work developed in this thesis has led us to suggest a robust identification algorithm, taking into account the intrinsic characteristics of the hand phalanges. Considered as hidden biometrics, this new approach can be of high interest, particularly when it comes to ensure a high level of security, robust to various attacks that a biometric system must address. The basis of the proposed techniques requires three phases, namely: (1) the segmentation of the phalanges (2) extracting their characteristics by generating an imprint, called "Phalange-Code" and (3) the identification based on the method of 1-nearest neighbor or the verification based on a similarity metric. This algorithm operates on hierarchical levels allowing the extraction of certain parameters invariant to geometric transformations such as image orientation and translation. Furthermore, the considered algorithm is particularly robust to noise, and can function at different resolutions of images. Thus, we developed three approaches to biometric recognition: the first approach produces individual signature from the spectral information of the contours issued from the hand phalanges, whereas the second approach requires the use of geometric and morphological characteristics of the phalanges (i.e. surface, perimeter, length, width, and capacity). Finally, the third approach requires the generation of a new likelihood ratio between the phalanges, using the geometric probability theory. Furthermore, the construction of a database with the lowest radiation dose was one of the great challenges of our study. We therefore proceeded with the collection of 403 x-ray images of the hand, acquired using the Apollo EZ X-Ray machine. These images are from 115 non-pathological volunteering adult (men and women). The average age is 27.2 years and the standard deviation is 8.5. Thus, the constructed database incorporates images of the right and left hands, acquired at different positions and by considering different resolutions and different radiation doses (i.e. reduced till 98% of the standard dose recommended by radiologists "1 µSv").Our experiments show that individuals can be distinguished by the characteristics of their phalanges, whether those of the right hand or the left hand. This distinction also applies to the kind of individuals (male/female). The study has demonstrated that the approach using the spectral information of the phalanges' contours allows identification by only three phalanges, with an EER (Equal Error Rate) lower than 0.24 %. Furthermore, it was found “Surprisingly” that the technique based on the likelihood ratio between phalanges reaches an identification rate of 100% and an EER of 0.37% with a single phalanx. Apart from the identification/authentication aspect, our study focused on the optimization of the radiation dose in order to offer safe identification of individuals. Thus, it has been shown that it was possible to acquire more than 12,500/year radiographic hand images, without exceeding the administrative control of 0.25 mSv
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Efficient Decoding of High-order Hidden Markov ModelsEngelbrecht, Herman A. 12 1900 (has links)
Thesis (PhD (Electrical and Electronic Engineering))--University of Stellenbosch, 2007. / Most speech recognition and language identification engines are based on hidden Markov
models (HMMs). Higher-order HMMs are known to be more powerful than first-order
HMMs, but have not been widely used because of their complexity and computational
demands. The main objective of this dissertation was to develop a more time-efficient
method of decoding high-order HMMs than the standard Viterbi decoding algorithm
currently in use.
We proposed, implemented and evaluated two decoders based on the Forward-Backward
Search (FBS) paradigm, which incorporate information obtained from low-order HMMs.
The first decoder is based on time-synchronous Viterbi-beam decoding where we wish
to base our state pruning on the complete observation sequence. The second decoder is
based on time-asynchronous A* search. The choice of heuristic is critical to the A* search
algorithms and a novel, task-independent heuristic function is presented. The experimental
results show that both these proposed decoders result in more time-efficient decoding
of the fully-connected, high-order HMMs that were investigated.
Three significant facts have been uncovered. The first is that conventional forward
Viterbi-beam decoding of high-order HMMs is not as computationally expensive as is
commonly thought.
The second (and somewhat surprising) fact is that backward decoding of conventional,
high-order left-context HMMs is significantly more expensive than the conventional forward
decoding. By developing the right-context HMM, we showed that the backward
decoding of a mathematically equivalent right-context HMM is as expensive as the forward
decoding of the left-context HMM.
The third fact is that the use of information obtained from low-order HMMs significantly
reduces the computational expense of decoding high-order HMMs. The comparison
of the two new decoders indicate that the FBS-Viterbi-beam decoder is more time-efficient
than the A* decoder. The FBS-Viterbi-beam decoder is not only simpler to implement,
it also requires less memory than the A* decoder.
We suspect that the broader research community regards the Viterbi-beam algorithm
as the most efficient method of decoding HMMs. We hope that the research presented
in this dissertation will result in renewed investigation into decoding algorithms that are
applicable to high-order HMMs.
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Bird song recognition with hidden Markov modelsVan der Merwe, Hugo Jacobus 03 1900 (has links)
Thesis (MScEng (Electrical and Electronic Engineering))--Stellenbosch University, 2008. / Automatic bird song recognition and transcription is a relatively new field. Reliable
automatic recognition systems would be of great benefit to further research
in ornithology and conservation, as well as commercially in the very large birdwatching
subculture.
This study investigated the use of Hidden Markov Models and duration
modelling for bird call recognition. Through use of more accurate duration
modelling, very promising results were achieved with feature vectors consisting
of only pitch and volume. An accuracy of 51% was achieved for 47 calls from 39
birds, with the models typically trained from only one or two specimens. The
ALS pitch tracking algorithm was adapted to bird song to extract the pitch.
Bird song synthesis was employed to subjectively evaluate the features.
Compounded Selfloop Duration Modelling was developed as an alternative
duration modelling technique. For long durations, this technique can be more
computationally efficient than Ferguson stacks.
The application of approximate string matching to bird song was also briefly
considered.
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An HMM-based automatic singing transcription platform for a sight-singing tutorKrige, Willie 03 1900 (has links)
Thesis (MScEng (Electrical and Electronic Engineering))--Stellenbosch University, 2008. / A singing transcription system transforming acoustic input into MIDI note sequences
is presented. The transcription system is incorporated into a pronunciation-independent
sight-singing tutor system, which provides note-level feedback on the accuracy with which
each note in a sequence has been sung.
Notes are individually modeled with hidden Markov models (HMMs) using untuned
pitch and delta-pitch as feature vectors. A database consisting of annotated passages
sung by 26 soprano subjects was compiled for the development of the system, since no
existing data was available. Various techniques that allow efficient use of a limited dataset
are proposed and evaluated. Several HMM topologies are also compared, in analogy with
approaches often used in the field of automatic speech recognition. Context-independent
note models are evaluated first, followed by the use of explicit transition models to better
identify boundaries between notes. A non-repetitive grammar is used to reduce the
number of insertions. Context-dependent note models are then introduced, followed by
context-dependent transition models. The aim in introducing context-dependency is to
improve transition region modeling, which in turn should increase note transcription accuracy,
but also improve the time-alignment of the notes and the transition regions. The
final system is found to be able to transcribe sung passages with around 86% accuracy.
Finally, a note-level sight-singing tutor system based on the singing transcription system
is presented and a number of note sequence scoring approaches are evaluated.
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