991 resultados para Digital signal
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Cyclic voltammetry has become one of the most useful tools in modern electrochemistry, but the use of digital potentiostats should be treated with caution by users. Staircase Voltammetry utilizes some parameters to build up the potential ramp. However, for some electrochemical processes, the signal response can be different compared with that acquired using true linear sweep (analogic signal). In this work, the role of SCV parameters in current response during the hydrogen electrochemical adsorption/desorption reaction on a platinum surface was studied. In addition, the transient current in each step comprising the ramp was investigated. The results showed that with a step height of 2 mV, the SCV response matches that recorded by linear sweep voltammetry. From the transient current study, two kinds of capacity were identified: non-faradaic and faradaic charge.
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Sähkökäytön suunnittelussa säätöä voidaan testata useassa tapauksessa reaaliaikasimulaattorilla todellisen laitteiston sijaan. Monet reaaliaikasimulaatioiden perustana käytetyt algoritmit soveltuvat täysinohjatulle invertterisillalle. Eräissä sovelluksissa halutaan kuitenkin käyttää puoliksiohjattua siltaa. Puoliksiohjattulla sillalla mallin kausaalisuus voi kääntyä, mitä perinteiset reaaliaikasimulaattorit eivät pysty simuloimaan Tässä työssä oli tavoitteena kehittää reaaliaikasimulaattori puoliksiohjatulle kestomagneettitahtikonekäytölle. Emulaattoriin mallinnettiin todellisen käytön kestomagneettitahtikone ja invertterisilta. Simulaattori toteutettiin digitaaliselle signaaliprosessorille (DSP) ja mittauksiin liittyvät oheislaitteet mallinnettiin FPGA-piirille. Emulaattoriin liitettiin erillinen säätäjä, jota käytettiin myös todellisen sähkökäytön säätämiseen. Emulaattorilla ja todellisella käytöllä tehtyjä mittauksia verrattiin ja emuloimalla saadut tulokset vastasivat melko hyvin todellisesta käytöstä mitattuja.
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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.
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La version intégrale de ce mémoire est disponible uniquement pour consultation individuelle à la Bibliothèque de musique de l'Université de Montréal (www.bib.umontreal.ca/MU).
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La radiothérapie stéréotaxique corporelle (SBRT) est une technique couramment employée pour le traitement de tumeurs aux poumons lorsque la chirurgie n’est pas possible ou refusée par le patient. Une complication de l’utilisation de cette méthode provient du mouvement de la tumeur causé par la respiration. Dans ce contexte, la radiothérapie asservie à la respiration (RGRT) peut être bénéfique. Toutefois, la RGRT augmente le temps de traitement en raison de la plus petite proportion de temps pour laquelle le faisceau est actif. En utilisant un faisceau de photons sans filtre égalisateur (FFF), ce problème peut être compensé par le débit de dose plus élevé d’un faisceau FFF. Ce mémoire traite de la faisabilité d’employer la technique de RGRT en combinaison avec l’utilisation un faisceau FFF sur un accélérateur Synergy S (Elekta, Stockholm, Suède) avec une ceinture pneumatique, le Bellows Belt (Philips, Amsterdam, Pays-Bas), comme dispositif de suivi du signal respiratoire. Un Synergy S a été modifié afin de pouvoir livrer un faisceau 6 MV FFF. Des mesures de profils de dose et de rendements en profondeur ont été acquises en cuve à eau pour différentes tailles de champs. Ces mesures ont été utilisées pour créer un modèle du faisceau 6 MV FFF dans le système de planification de traitement Pinnacle3 de Philips. Les mesures ont été comparées au modèle à l’aide de l’analyse gamma avec un critère de 2%, 2 mm. Par la suite, cinq plans SBRT avec thérapie en arc par modulation volumétrique (VMAT) ont été créés avec le modèle 6 MV du Synergy S, avec et sans filtre. Une comparaison des paramètres dosimétriques a été réalisée entre les plans avec et sans filtre pour évaluer la qualité des plans FFF. Les résultats révèlent qu’il est possible de créer des plans SBRT VMAT avec le faisceau 6 MV FFF du Synergy S qui sont cliniquement acceptables (les crières du Radiation Therapy Oncology Group 0618 sont respectés). Aussi, une interface physique de RGRT a été mise au point pour remplir deux fonctions : lire le signal numérique de la ceinture pneumatique Bellows Belt et envoyer une commande d’irradiation binaire au linac. L’activation/désactivation du faisceau du linac se fait par l’entremise d’un relais électromécanique. L’interface comprend un circuit électronique imprimé fait maison qui fonctionne en tandem avec un Raspberry Pi. Un logiciel de RGRT a été développé pour opérer sur le Raspberry Pi. Celui-ci affiche le signal numérique du Bellows Belt et donne l’option de choisir les limites supérieure et inférieure de la fenêtre d’irradiation, de sorte que lorsque le signal de la ceinture se trouve entre ces limites, le faisceau est actif, et inversement lorsque le signal est hors de ces limites. Le logiciel envoie donc une commande d’irradiation au linac de manière automatique en fonction de l’amplitude du signal respiratoire. Finalement, la comparaison entre la livraison d’un traitement standard sans RGRT avec filtre par rapport à un autre plan standard sans RGRT sans filtre démontre que le temps de traitement en mode FFF est réduit en moyenne de 54.1% pour un arc. De la même manière, la comparaison entre la livraison d’un traitement standard sans RGRT avec filtre par rapport à un plan de RGRT (fenêtre d’irradiation de 75%) sans filtre montre que le temps de traitement de RGRT en mode FFF est réduit en moyenne de 27.3% par arc. Toutefois, il n’a pas été possible de livrer des traitements de RGRT avec une fenêtre de moins de 75%. Le linac ne supporte pas une fréquence d’arrêts élevée.
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Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation. Current implementations of these functions rely on conventional techniques largely based on Fourier Techniques, primarily meant for stationary signals. Interestingly enough, the signals received by the sonar sensors are often non-stationary and hence processing methods capable of handling the non-stationarity will definitely fare better than Fourier transform based methods.Time-frequency methods(TFMs) are known as one of the best DSP tools for nonstationary signal processing, with which one can analyze signals in time and frequency domains simultaneously. But, other than STFT, TFMs have been largely limited to academic research because of the complexity of the algorithms and the limitations of computing power. With the availability of fast processors, many applications of TFMs have been reported in the fields of speech and image processing and biomedical applications, but not many in sonar processing. A structured effort, to fill these lacunae by exploring the potential of TFMs in sonar applications, is the net outcome of this thesis. To this end, four TFMs have been explored in detail viz. Wavelet Transform, Fractional Fourier Transfonn, Wigner Ville Distribution and Ambiguity Function and their potential in implementing five major sonar functions has been demonstrated with very promising results. What has been conclusively brought out in this thesis, is that there is no "one best TFM" for all applications, but there is "one best TFM" for each application. Accordingly, the TFM has to be adapted and tailored in many ways in order to develop specific algorithms for each of the applications.
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Fourier transform methods are employed heavily in digital signal processing. Discrete Fourier Transform (DFT) is among the most commonly used digital signal transforms. The exponential kernel of the DFT has the properties of symmetry and periodicity. Fast Fourier Transform (FFT) methods for fast DFT computation exploit these kernel properties in different ways. In this thesis, an approach of grouping data on the basis of the corresponding phase of the exponential kernel of the DFT is exploited to introduce a new digital signal transform, named the M-dimensional Real Transform (MRT), for l-D and 2-D signals. The new transform is developed using number theoretic principles as regards its specific features. A few properties of the transform are explored, and an inverse transform presented. A fundamental assumption is that the size of the input signal be even. The transform computation involves only real additions. The MRT is an integer-to-integer transform. There are two kinds of redundancy, complete redundancy & derived redundancy, in MRT. Redundancy is analyzed and removed to arrive at a more compact version called the Unique MRT (UMRT). l-D UMRT is a non-expansive transform for all signal sizes, while the 2-D UMRT is non-expansive for signal sizes that are powers of 2. The 2-D UMRT is applied in image processing applications like image compression and orientation analysis. The MRT & UMRT, being general transforms, will find potential applications in various fields of signal and image processing.
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The proliferation of wireless sensor networks in a large spectrum of applications had been spurered by the rapid advances in MEMS(micro-electro mechanical systems )based sensor technology coupled with low power,Low cost digital signal processors and radio frequency circuits.A sensor network is composed of thousands of low cost and portable devices bearing large sensing computing and wireless communication capabilities. This large collection of tiny sensors can form a robust data computing and communication distributed system for automated information gathering and distributed sensing.The main attractive feature is that such a sensor network can be deployed in remote areas.Since the sensor node is battery powered,all the sensor nodes should collaborate together to form a fault tolerant network so as toprovide an efficient utilization of precious network resources like wireless channel,memory and battery capacity.The most crucial constraint is the energy consumption which has become the prime challenge for the design of long lived sensor nodes.
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Median filtering is a simple digital non—linear signal smoothing operation in which median of the samples in a sliding window replaces the sample at the middle of the window. The resulting filtered sequence tends to follow polynomial trends in the original sample sequence. Median filter preserves signal edges while filtering out impulses. Due to this property, median filtering is finding applications in many areas of image and speech processing. Though median filtering is simple to realise digitally, its properties are not easily analysed with standard analysis techniques,
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Speech processing and consequent recognition are important areas of Digital Signal Processing since speech allows people to communicate more natu-rally and efficiently. In this work, a speech recognition system is developed for re-cognizing digits in Malayalam. For recognizing speech, features are to be ex-tracted from speech and hence feature extraction method plays an important role in speech recognition. Here, front end processing for extracting the features is per-formed using two wavelet based methods namely Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Naive Bayes classifier is used for classification purpose. After classification using Naive Bayes classifier, DWT produced a recognition accuracy of 83.5% and WPD produced an accuracy of 80.7%. This paper is intended to devise a new feature extraction method which produces improvements in the recognition accuracy. So, a new method called Dis-crete Wavelet Packet Decomposition (DWPD) is introduced which utilizes the hy-brid features of both DWT and WPD. The performance of this new approach is evaluated and it produced an improved recognition accuracy of 86.2% along with Naive Bayes classifier.
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DNA sequence representation methods are used to denote a gene structure effectively and help in similarities/dissimilarities analysis of coding sequences. Many different kinds of representations have been proposed in the literature. They can be broadly classified into Numerical, Graphical, Geometrical and Hybrid representation methods. DNA structure and function analysis are made easy with graphical and geometrical representation methods since it gives visual representation of a DNA structure. In numerical method, numerical values are assigned to a sequence and digital signal processing methods are used to analyze the sequence. Hybrid approaches are also reported in the literature to analyze DNA sequences. This paper reviews the latest developments in DNA Sequence representation methods. We also present a taxonomy of various methods. A comparison of these methods where ever possible is also done
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This paper compares the most common digital signal processing methods of exon prediction in eukaryotes, and also proposes a technique for noise suppression in exon prediction. The specimen used here which has relevance in medical research, has been taken from the public genomic database - GenBank.Here exon prediction has been done using the digital signal processing methods viz. binary method, EIIP (electron-ion interaction psuedopotential) method and filter methods. Under filter method two filter designs, and two approaches using these two designs have been tried. The discrete wavelet transform has been used for de-noising of the exon plots.Results of exon prediction based on the methods mentioned above, which give values closest to the ones found in the NCBI database are given here. The exon plot de-noised using discrete wavelet transform is also given.Alterations to the proven methods as done by the authors, improves performance of exon prediction algorithms. Also it has been proven that the discrete wavelet transform is an effective tool for de-noising which can be used with exon prediction algorithms
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The basic concepts of digital signal processing are taught to the students in engineering and science. The focus of the course is on linear, time invariant systems. The question as to what happens when the system is governed by a quadratic or cubic equation remains unanswered in the vast majority of literature on signal processing. Light has been shed on this problem when John V Mathews and Giovanni L Sicuranza published the book Polynomial Signal Processing. This book opened up an unseen vista of polynomial systems for signal and image processing. The book presented the theory and implementations of both adaptive and non-adaptive FIR and IIR quadratic systems which offer improved performance than conventional linear systems. The theory of quadratic systems presents a pristine and virgin area of research that offers computationally intensive work. Once the area of research is selected, the next issue is the choice of the software tool to carry out the work. Conventional languages like C and C++ are easily eliminated as they are not interpreted and lack good quality plotting libraries. MATLAB is proved to be very slow and so do SCILAB and Octave. The search for a language for scientific computing that was as fast as C, but with a good quality plotting library, ended up in Python, a distant relative of LISP. It proved to be ideal for scientific computing. An account of the use of Python, its scientific computing package scipy and the plotting library pylab is given in the appendix Initially, work is focused on designing predictors that exploit the polynomial nonlinearities inherent in speech generation mechanisms. Soon, the work got diverted into medical image processing which offered more potential to exploit by the use of quadratic methods. The major focus in this area is on quadratic edge detection methods for retinal images and fingerprints as well as de-noising raw MRI signals
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The transreal numbers are a total number system in which even, arithmetical operation is well defined even-where. This has many benefits over the real numbers as a basis for computation and, possibly, for physical theories. We define the topology of the transreal numbers and show that it gives a more coherent interpretation of two's complement arithmetic than the conventional integer model. Trans-two's-complement arithmetic handles the infinities and 0/0 more coherently, and with very much less circuitry, than floating-point arithmetic. This reduction in circuitry is especially beneficial in parallel computers, such as the Perspex machine, and the increase in functionality makes Digital Signal Processing chips better suited to general computation.
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Frequency recognition is an important task in many engineering fields such as audio signal processing and telecommunications engineering, for example in applications like Dual-Tone Multi-Frequency (DTMF) detection or the recognition of the carrier frequency of a Global Positioning, System (GPS) signal. This paper will present results of investigations on several common Fourier Transform-based frequency recognition algorithms implemented in real time on a Texas Instruments (TI) TMS320C6713 Digital Signal Processor (DSP) core. In addition, suitable metrics are going to be evaluated in order to ascertain which of these selected algorithms is appropriate for audio signal processing(1).