Programació d'una aplicació grà fica per l'anà lisi de senyals usant LDB (Local Discriminant Bases) i MLDB (Modified LDB)

Tot seguit presentem un entorn per analitzar senyals de tot tipus amb LDB (Local Discriminant Bases) i MLDB (Modified Local Discriminant Bases). Aquest entorn utilitza funcions desenvolupades en el marc d’una tesi en fase de desenvolupament. Per entendre part d’aquestes funcions es requereix un nivell de coneixement avançat de processament de senyals. S’han extret dels treballs realitzats per Naoki Saito [3], que s’han agafat com a punt de partida per la realització de l’algorisme de la tesi doctoral no finalitzada de Jose Antonio Soria. Aquesta interfície desenvolupada accepta la incorporació de nous paquets i funcions. Hem deixat un menú preparat per integrar Sinus IV packet transform i Cosine IV packet transform, tot i que també podem incorporar-n’hi altres. L’aplicació consta de dues interfícies, un Assistent i una interfície principal. També hem creat una finestra per importar i exportar les variables desitjades a diferents entorns. Per fer aquesta aplicació s’han programat tots els elements de les finestres, en lloc d’utilitzar el GUIDE (Graphical User Interface Development Enviroment) de MATLAB, per tal que sigui compatible entre les diferents versions d’aquest programa. En total hem fet 73 funcions en la interfície principal (d’aquestes, 10 pertanyen a la finestra d’importar i exportar) i 23 en la de l’Assistent. En aquest treball només explicarem 6 funcions i les 3 de creació d’aquestes interfícies per no fer-lo excessivament extens. Les funcions que explicarem són les més importants, ja sigui perquè s’utilitzen sovint, perquè, segons la complexitat McCabe, són les més complicades o perquè són necessàries pel processament del senyal. Passem cada entrada de dades per part de l’usuari per funcions que ens detectaran errors en aquesta entrada, com eliminació de zeros o de caràcters que no siguin números, com comprovar que són enters o que estan dins dels límits màxims i mínims que li pertoquen.

Combined application of continuous wavelet transform-zero crossing technique in the simultaneous spectrophotometric determination of perindopril and indapamid in tablets

Signal processing methods based on the combined use of the continuous wavelet transform (CWT) and zero-crossing technique were applied to the simultaneous spectrophotometric determination of perindopril (PER) and indapamide (IND) in tablets. These signal processing methods do not require any priory separation step. Initially, various wavelet families were tested to identify the optimum signal processing giving the best recovery results. From this procedure, the Haar and Biorthogonal1.5 continuous wavelet transform (HAAR-CWT and BIOR1.5-CWT, respectively) were found suitable for the analysis of the related compounds. After transformation of the absorbance vectors by using HAAR-CWT and BIOR1.5-CWT, the CWT-coefficients were drawn as a graph versus wavelength and then the HAAR-CWT and BIOR1.5-CWT spectra were obtained. Calibration graphs for PER and IND were obtained by measuring the CWT amplitudes at 231.1 and 291.0 nm in the HAAR-CWT spectra and at 228.5 and 246.8 nm in BIOR1.5-CWT spectra, respectively. In order to compare the performance of HAAR-CWT and BIOR1.5-CWT approaches, derivative spectrophotometric (DS) method and HPLC as comparison methods, were applied to the PER-IND samples. In this DS method, first derivative absorbance values at 221.6 for PER and 282.7 nm for IND were used to obtain the calibration graphs. The validation of the CWT and DS signal processing methods was carried out by using the recovery study and standard addition technique. In the following step, these methods were successfully applied to the commercial tablets containing PER and IND compounds and good accuracy and precision were reported for the experimental results obtained by all proposed signal processing methods.

D-luokan audiovahvistimen modulointimenetelmien vertailu ja valinta

Tässä työssä esitellään kaksi D-luokan audiovahvistimissa käytettyä modulointimenetelmää ja vertaillaan niiden välisiä ominaisuuksia. Esitellyt menetelmät ovat pulssinleveysmodulaatio sekä sigma-deltamodulaatio. Lisäksi työssä esitellään signaalin käsittelyssä muodostuvan kohinan ja särön syntyä ja menetelmiä niiden välttämiseksi. Menetelmien ominaisuuksien vertailuun muodostetaan simulointimallit Simulink-ohjelmalla. Simulointitulosten perusteella valitaan käytettävä modulointimenetelmä audiovahvistinsovellukseen huomioon ottaen asetetut vaatimukset ja tavoitteet. Lopuksi valitun modulointimenetelmän suunnittelun pääkohtiin kiinnitetään huomiota.

Akustisen emission anturin signaalin esikäsittelypiirin selvittäminen ja prototyypin toteuttaminen

Tämän työn tavoitteena oli selvittää ja toteuttaa esikäsittelypiirin prototyyppi akustisen emission anturin signaalille. Toteutettu esikäsittelypiiri toimii yksipuoleisella käyttöjännitteellä. Työssä käydään läpi esikäsittelypiirin suunnitteluun liittyvät vaiheet laskelmien ja simulaatioiden muodossa. Lisäksi työssä esitetään mittaustulokset esikäsittelypiirin toiminnasta.

Vibration analysis for Bearing outer race condition diagnostics

This paper investigates defect detection methodologies for rolling element bearings through vibration analysis. Specifically, the utility of a new signal processing scheme combining the High Frequency Resonance Technique (HFRT) and Adaptive Line Enhancer (ALE) is investigated. The accelerometer is used to acquire data for this analysis, and experimental results have been obtained for outer race defects. Results show the potential effectiveness of the signal processing technique to determine both the severity and location of a defect. The HFRT utilizes the fact that much of the energy resulting from a defect impact manifests itself in the higher resonant frequencies of a system. Demodulation of these frequency bands through use of the envelope technique is then employed to gain further insight into the nature of the defect while further increasing the signal to noise ratio. If periodic, the defect frequency is then present in the spectra of the enveloped signal. The ALE is used to enhance the envelope spectrum by reducing the broadband noise. It provides an enhanced envelope spectrum with clear peaks at the harmonics of a characteristic defect frequency. It is implemented by using a delayed version of the signal and the signal itself to decorrelate the wideband noise. This noise is then rejected by the adaptive filter that is based upon the periodic information in the signal. Results have been obtained for outer race defects. They show the effectiveness of the methodology to determine both the severity and location of a defect. In two instances, a linear relationship between signal characteristics and defect size is indicated.

Chaotic Behaviour of Active Magnetic Bearing System by Time Series Analysis

Chaotic behaviour is one of the hardest problems that can happen in nonlinear dynamical systems with severe nonlinearities. It makes the system's responses unpredictable. It makes the system's responses to behave similar to noise. In some applications it should be avoided. One of the approaches to detect the chaotic behaviour is nding the Lyapunov exponent through examining the dynamical equation of the system. It needs a model of the system. The goal of this study is the diagnosis of chaotic behaviour by just exploring the data (signal) without using any dynamical model of the system. In this work two methods are tested on the time series data collected from AMB (Active Magnetic Bearing) system sensors. The rst method is used to nd the largest Lyapunov exponent by Rosenstein method. The second method is a 0-1 test for identifying chaotic behaviour. These two methods are used to detect if the data is chaotic. By using Rosenstein method it is needed to nd the minimum embedding dimension. To nd the minimum embedding dimension Cao method is used. Cao method does not give just the minimum embedding dimension, it also gives the order of the nonlinear dynamical equation of the system and also it shows how the system's signals are corrupted with noise. At the end of this research a test called runs test is introduced to show that the data is not excessively noisy.

Variable speed drive in fan system monitoring

Fan systems are responsible for approximately 10% of the electricity consumption in industrial and municipal sectors, and it has been found that there is energy-saving potential in these systems. To this end, variable speed drives (VSDs) are used to enhance the efficiency of fan systems. Usually, fan system operation is optimized based on measurements of the system, but there are seldom readily installed meters in the system that can be used for the purpose. Thus, sensorless methods are needed for the optimization of fan system operation. In this thesis, methods for the fan operating point estimation with a variable speed drive are studied and discussed. These methods can be used for the energy efficient control of the fan system without additional measurements. The operation of these methods is validated by laboratory measurements and data from an industrial fan system. In addition to their energy consumption, condition monitoring of fan systems is a key issue as fans are an integral part of various production processes. Fan system condition monitoring is usually carried out with vibration measurements, which again increase the system complexity. However, variable speed drives can already be used for pumping system condition monitoring. Therefore, it would add to the usability of a variablespeed- driven fan system if the variable speed drive could be used as a condition monitoring device. In this thesis, sensorless detection methods for three lifetime-reducing phenomena are suggested: these are detection of the fan contamination build-up, the correct rotational direction, and the fan surge. The methods use the variable speed drive monitoring and control options for the detection along with simple signal processing methods, such as power spectrum density estimates. The methods have been validated by laboratory measurements. The key finding of this doctoral thesis is that a variable speed drive can be used on its own as a monitoring and control device for the fan system energy efficiency, and it can also be used in the detection of certain lifetime-reducing phenomena.

Linear prediction in optical spectroscopy

A linear prediction procedure is one of the approved numerical methods of signal processing. In the field of optical spectroscopy it is used mainly for extrapolation known parts of an optical signal in order to obtain a longer one or deduce missing signal samples. The first is needed particularly when narrowing spectral lines for the purpose of spectral information extraction. In the present paper the coherent anti-Stokes Raman scattering (CARS) spectra were under investigation. The spectra were significantly distorted by the presence of nonlinear nonresonant background. In addition, line shapes were far from Gaussian/Lorentz profiles. To overcome these disadvantages the maximum entropy method (MEM) for phase spectrum retrieval was used. The obtained broad MEM spectra were further underwent the linear prediction analysis in order to be narrowed.

Scheduling dynamic dataflow graphs with model checking

With the shift towards many-core computer architectures, dataflow programming has been proposed as one potential solution for producing software that scales to a varying number of processor cores. Programming for parallel architectures is considered difficult as the current popular programming languages are inherently sequential and introducing parallelism is typically up to the programmer. Dataflow, however, is inherently parallel, describing an application as a directed graph, where nodes represent calculations and edges represent a data dependency in form of a queue. These queues are the only allowed communication between the nodes, making the dependencies between the nodes explicit and thereby also the parallelism. Once a node have the su cient inputs available, the node can, independently of any other node, perform calculations, consume inputs, and produce outputs. Data ow models have existed for several decades and have become popular for describing signal processing applications as the graph representation is a very natural representation within this eld. Digital lters are typically described with boxes and arrows also in textbooks. Data ow is also becoming more interesting in other domains, and in principle, any application working on an information stream ts the dataflow paradigm. Such applications are, among others, network protocols, cryptography, and multimedia applications. As an example, the MPEG group standardized a dataflow language called RVC-CAL to be use within reconfigurable video coding. Describing a video coder as a data ow network instead of with conventional programming languages, makes the coder more readable as it describes how the video dataflows through the different coding tools. While dataflow provides an intuitive representation for many applications, it also introduces some new problems that need to be solved in order for data ow to be more widely used. The explicit parallelism of a dataflow program is descriptive and enables an improved utilization of available processing units, however, the independent nodes also implies that some kind of scheduling is required. The need for efficient scheduling becomes even more evident when the number of nodes is larger than the number of processing units and several nodes are running concurrently on one processor core. There exist several data ow models of computation, with different trade-offs between expressiveness and analyzability. These vary from rather restricted but statically schedulable, with minimal scheduling overhead, to dynamic where each ring requires a ring rule to evaluated. The model used in this work, namely RVC-CAL, is a very expressive language, and in the general case it requires dynamic scheduling, however, the strong encapsulation of dataflow nodes enables analysis and the scheduling overhead can be reduced by using quasi-static, or piecewise static, scheduling techniques. The scheduling problem is concerned with nding the few scheduling decisions that must be run-time, while most decisions are pre-calculated. The result is then an, as small as possible, set of static schedules that are dynamically scheduled. To identify these dynamic decisions and to find the concrete schedules, this thesis shows how quasi-static scheduling can be represented as a model checking problem. This involves identifying the relevant information to generate a minimal but complete model to be used for model checking. The model must describe everything that may affect scheduling of the application while omitting everything else in order to avoid state space explosion. This kind of simplification is necessary to make the state space analysis feasible. For the model checker to nd the actual schedules, a set of scheduling strategies are de ned which are able to produce quasi-static schedulers for a wide range of applications. The results of this work show that actor composition with quasi-static scheduling can be used to transform data ow programs to t many different computer architecture with different type and number of cores. This in turn, enables dataflow to provide a more platform independent representation as one application can be fitted to a specific processor architecture without changing the actual program representation. Instead, the program representation is in the context of design space exploration optimized by the development tools to fit the target platform. This work focuses on representing the dataflow scheduling problem as a model checking problem and is implemented as part of a compiler infrastructure. The thesis also presents experimental results as evidence of the usefulness of the approach.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Heart rate variability under resting conditions in postmenopausal and young women

The aim of the present study was to compare the modulation of heart rate in a group of postmenopausal women to that of a group of young women under resting conditions on the basis of R-R interval variability. Ten healthy postmenopausal women (mean ± SD, 58.3 ± 6.8 years) and 10 healthy young women (mean ± SD, 21.6 ± 0.82 years) were submitted to a control resting electrocardiogram (ECG) in the supine and sitting positions over a period of 6 min. The ECG was obtained from a one-channel heart monitor at the CM5 lead and processed and stored using an analog to digital converter connected to a microcomputer. R-R intervals were calculated on a beat-to-beat basis from the ECG recording in real time using a signal-processing software. Heart rate variability (HRV) was expressed as standard deviation (RMSM) and mean square root (RMSSD). In the supine position, the postmenopausal group showed significantly lower (P<0.05) median values of RMSM (34.9) and RMSSD (22.32) than the young group (RMSM: 62.11 and RMSSD: 49.1). The same occurred in the sitting position (RMSM: 33.0 and RMSSD: 18.9 compared to RMSM: 57.6 and RMSSD: 42.8 for the young group). These results indicate a decrease in parasympathetic modulation in postmenopausal women compared to young women which was possibly due both to the influence of age and hormonal factors. Thus, time domain HRV proved to be a noninvasive and sensitive method for the identification of changes in autonomic modulation of the sinus node in postmenopausal women.

Computerized invasive measurement of time-dependent intraocular pressure

Several methods have been described to measure intraocular pressure (IOP) in clinical and research situations. However, the measurement of time varying IOP with high accuracy, mainly in situations that alter corneal properties, has not been reported until now. The present report describes a computerized system capable of recording the transitory variability of IOP, which is sufficiently sensitive to reliably measure ocular pulse peak-to-peak values. We also describe its characteristics and discuss its applicability to research and clinical studies. The device consists of a pressure transducer, a signal conditioning unit and an analog-to-digital converter coupled to a video acquisition board. A modified Cairns trabeculectomy was performed in 9 Oryctolagus cuniculus rabbits to obtain changes in IOP decay parameters and to evaluate the utility and sensitivity of the recording system. The device was effective for the study of kinetic parameters of IOP, such as decay pattern and ocular pulse waves due to cardiac and respiratory cycle rhythm. In addition, there was a significant increase of IOP versus time curve derivative when pre- and post-trabeculectomy recordings were compared. The present procedure excludes corneal thickness and error related to individual operator ability. Clinical complications due to saline infusion and pressure overload were not observed during biomicroscopic evaluation. Among the disadvantages of the procedure are the requirement of anesthesia and the use in acute recordings rather than chronic protocols. Finally, the method described may provide a reliable alternative for the study of ocular pressure dynamic alterations in man and may facilitate the investigation of the pathogenesis of glaucoma.

Statistical analysis of event-related potential elicited by verb-complement merge in Brazilian Portuguese

An interesting fact about language cognition is that stimulation involving incongruence in the merge operation between verb and complement has often been related to a negative event-related potential (ERP) of augmented amplitude and latency of ca. 400 ms - the N400. Using an automatic ERP latency and amplitude estimator to facilitate the recognition of waves with a low signal-to-noise ratio, the objective of the present study was to study the N400 statistically in 24 volunteers. Stimulation consisted of 80 experimental sentences (40 congruous and 40 incongruous), generated in Brazilian Portuguese, involving two distinct local verb-argument combinations (nominal object and pronominal object series). For each volunteer, the EEG was simultaneously acquired at 20 derivations, topographically localized according to the 10-20 International System. A computerized routine for automatic N400-peak marking (based on the ascendant zero-cross of the first waveform derivative) was applied to the estimated individual ERP waveform for congruous and incongruous sentences in both series for all ERP topographic derivations. Peak-to-peak N400 amplitude was significantly augmented (P < 0.05; one-sided Wilcoxon signed-rank test) due to incongruence in derivations F3, T3, C3, Cz, T5, P3, Pz, and P4 for nominal object series and in P3, Pz and P4 for pronominal object series. The results also indicated high inter-individual variability in ERP waveforms, suggesting that the usual procedure of grand averaging might not be considered a generally adequate approach. Hence, signal processing statistical techniques should be applied in neurolinguistic ERP studies allowing waveform analysis with low signal-to-noise ratio.

Comparison of the Polar S810i monitor and the ECG for the analysis of heart rate variability in the time and frequency domains

The aim of the present study was to compare heart rate variability (HRV) at rest and during exercise using a temporal series obtained with the Polar S810i monitor and a signal from a LYNX® signal conditioner (BIO EMG 1000 model) with a channel configured for the acquisition of ECG signals. Fifteen healthy subjects aged 20.9 ± 1.4 years were analyzed. The subjects remained at rest for 20 min and performed exercise for another 20 min with the workload selected to achieve 60% of submaximal heart rate. RR series were obtained for each individual with a Polar S810i instrument and with an ECG analyzed with a biological signal conditioner. The HRV indices (rMSSD, pNN50, LFnu, HFnu, and LF/HF) were calculated after signal processing and analysis. The unpaired Student t-test and intraclass correlation coefficient were used for data analysis. No statistically significant differences were observed when comparing the values analyzed by means of the two devices for HRV at rest and during exercise. The intraclass correlation coefficient demonstrated satisfactory correlation between the values obtained by the devices at rest (pNN50 = 0.994; rMSSD = 0.995; LFnu = 0.978; HFnu = 0.978; LF/HF = 0.982) and during exercise (pNN50 = 0.869; rMSSD = 0.929; LFnu = 0.973; HFnu = 0.973; LF/HF = 0.942). The calculation of HRV values by means of temporal series obtained from the Polar S810i instrument appears to be as reliable as those obtained by processing the ECG signal captured with a signal conditioner.

The effect of gregarine parasite infections, age, and diet on calling song structure and mating behaviour in the Texas field cricket, Gryllus integer

In the past ten years, many researchers have focussed their attention on parasites regarding the role they may play in causing variations in male secondary sexual traits and subsequent effects on female choice. Male age has also been suggested to be an important factor in female choice if old age reflects superior genes. This study investigated the effects that gregarine gut parasites, age, and diet have on the calling and mating behaviour of the male Texas field cricket, Gryllus integer. Male calling songs were recorded in the laboratory using a Digital Signal Processing Network. The song parameters measured were: pulse rate, pulse width, burst duration, pulses per burst, interburst interval, and percent missing pulses. The effects of parasite load and age on the various calling song parameters was investigated in crickets that were fed two different diets varying in nutritional quality. None of the calling song parameters were affected by either parasite load or age in either diet grou p. Courtship behaviour was ob served and recorded using an Eventlog recorder on an IBM computer in the laboratory. Females mated equally with paras(tized and unparasitized males and with old and young males The total duration and proportion of time spent performing each of 9 courtship displays were recorded for males on each diet. Only one display was affected by parasite load. Highly parasitized males fed the nutritionally inferior diet juddered for a proportionately shorter time than males with low parasite loads. Also, older males performed juddering and shaking antennae proportionally longer and juddering and raising wings for longer durations than younger males. Males that successfully mated were observed for performance of 8 post-copulatory guarding behaviour displays. None of the guarding behaviours were affected by parasite load. However, one display was affected by age, with older males performing guard turning for shorter durations than younger males. Results are discuss,ed in terms of the influence of parasites and age on female choice.