Adaptive Detection of Instabilities: An Experimental Feasibility Study

We present an example of the practical implementation of a protocol for experimental bifurcation detection based on on-line identification and feedback control ideas. The idea is to couple the experiment with an on-line computer-assisted identification/feedback protocol so that the closed-loop system will converge to the open-loop bifurcation points. We demonstrate the applicability of this instability detection method by real-time, computer-assisted detection of period doubling bifurcations of an electronic circuit; the circuit implements an analog realization of the Roessler system. The method succeeds in locating the bifurcation points even in the presence of modest experimental uncertainties, noise and limited resolution. The results presented here include bifurcation detection experiments that rely on measurements of a single state variable and delay-based phase space reconstruction, as well as an example of tracing entire segments of a codimension-1 bifurcation boundary in two parameter space.Comment: 29 pages, Latex 2.09, 10 figures in encapsulated postscript format (eps), need psfig macro to include them. Submitted to Physica

PCAdmix: Principal Components-Based Assignment of Ancestry along Each Chromosome in Individuals with Admixed Ancestry from Two or More Populations

Identifying ancestry along each chromosome in admixed individuals provides a wealth of information for understanding the population genetic history of admixture events and is valuable for admixture mapping and identifying recent targets of selection. We present PCAdmix (available at https://sites.google.com/site/pcadmix/home), a Principal Componentsbased algorithm for determining ancestry along each chromosome from a high-density, genome-wide set of phased single-nucleotide polymorphism (SNP) genotypes of admixed individuals. We compare our method to HAPMIX on simulated data from two ancestral populations, and we find high concordance between the methods. Our method also has better accuracy than LAMP when applied to three-population admixture, a situation as yet unaddressed by HAPMIX. Finally, we apply our method to a data set of four Latino populations with European, African, and Native American ancestry. We find evidence of assortative mating in each of the four populations, and we identify regions of shared ancestry that may be recent targets of selection and could serve as candidate regions for admixture-based association mapping

Applying Language Technology in ErrorDetection for Optical Music Recognition

Etter fremveksten av teknikker som benytter dyp læring har Optical Music Recognition-løsninger som forsøker å lese og forstå noter sett store fremskritt. Teknikker som benytter dyp læring er ofte vanskelig å validere, noe som er et viktig skritt for å sikre korrektheten til en løsning. Det er vanlig å validere slike løsninger ved å sammenligne resultatene med håndlagde eller datagenererte fasiter. Dette krever at datasettene er av høy kvalitet, og at alle fasitene er korrekte. Ved å benytte veletablert teknologi som språkteori og kompilatorkonstruksjon kan en tilnærming som modellerer problemet være mer nøyaktig og mindre arbeidskrevenede enn den vanlig tilnærmingen innen dyp læring. Ved å modellere resultatdomenet kan man oppnå både lett og effektiv bekreftelse. Dette fjerner behovet for å skape fasiter for ethvert tilfelle. En ekstra fordel med dette er at det fjerner feilkilder, for eksempel feiltrykk i notene eller at testene ikke dekker alle tilfeller. En eksisterende grammatikk fra tidligere arbeider ble gjort om og en kompilator front-end ble implementert. I tillegg ble det også utført en studie av formelle språk for å finne nye og elegante måter å utvide grammatikken på. Dette ga gode resultater. Kompilatoren ble testet på datasettet PRiMuS og viste en feilrate på bare 0,14%, som betyr at det er en god representasjon av det resultatdomenet. Noen av disse feilene viste seg å være tidligere urapporterte feil i datasettet som nå kan fjernes eller fikses.With the rise of deep learning techniques, Optical Music Recognition software that aims to read and understand musical notation has seen great progress. However, deep learning techniques are often difficult to validate, which is a crucial step in order to ensure the correctness of a solution. It is common to validate deep learning solutions by comparing results to hand crafted or computer generated ground truth representations. This requires the quality of the data sets to be very high, as well as every ground truth representation to be correct. By utilizing well established technology like language theory and compiler construction, a modelling approach can prove to be more accurate and less labour intensive than the common practice in deep learning today. Creating a model of the result domain may lead to both easy and efficient verification. This eliminates the need for creating ground truth representations to cover every scenario. An added benefit of this is that it removes many sources of errors, such as misprints and lack of coverage in the tests. An existing grammar was reworked and a compiler front-end was implemented. Additionally, a study of formal languages was also conducted in order to find new and elegant ways of extending the grammar. This yielded good results. The compiler front-end was tested on the PRiMuS dataset and exhibited an error rate of only 0.14%, which indicates a good representation of the intended language. Some of these errors turned out to be previously unreported errors in the data set, which can now be removed or fixed

Presurgical planning through the application of neuronavigated transcranial magnetic stimulation of secondary motor areas and speech areas

Masteroppgave i psykologiMAPSYK360INTL-SVINTL-JUSINTL-MNINTL-KMDINTL-PSYKMAPS-PSYKINTL-HFINTL-ME

Self-tuning to the Hopf bifurcation in fluctuating systems

The problem of self-tuning a system to the Hopf bifurcation in the presence of noise and periodic external forcing is discussed. We find that the response of the system has a non-monotonic dependence on the noise-strength, and displays an amplified response which is more pronounced for weaker signals. The observed effect is to be distinguished from stochastic resonance. For the feedback we have studied, the unforced self-tuned Hopf oscillator in the presence of fluctuations exhibits sharp peaks in its spectrum. The implications of our general results are briefly discussed in the context of sound detection by the inner ear.Comment: 37 pages, 7 figures (8 figure files