Novel method to improve the signal-to-noise ratio in the far-field results obtained from planar near-field measurements

A method to reduce the noise power in far-field pattern without modifying the desired signal is proposed. Therefore, an important signal-to-noise ratio improvement may be achieved. The method is used when the antenna measurement is performed in planar near-field, where the recorded data are assumed to be corrupted with white Gaussian and space-stationary noise, because of the receiver additive noise. Back-propagating the measured field from the scan plane to the antenna under test (AUT) plane, the noise remains white Gaussian and space-stationary, whereas the desired field is theoretically concentrated in the aperture antenna. Thanks to this fact, a spatial filtering may be applied, cancelling the field which is located out of the AUT dimensions and which is only composed by noise. Next, a planar field to far-field transformation is carried out, achieving a great improvement compared to the pattern obtained directly from the measurement. To verify the effectiveness of the method, two examples will be presented using both simulated and measured near-field data.

Alarm tree analysis using statistical techniques

This work presents a systematic method for the generation and treatment of the alarms' graphs, being its final object to find the Alarm Root Cause of the Massive Alarms that are produced in the dispatching centers. Although many works about this matter have been already developed, the problem about the alarm management in the industry is still completely unsolved. In this paper, a simple statistic analysis of the historical data base is conducted. The results obtained by the acquisition alarm systems, are used to generate a directed graph from which the more significant alarms are extracted, previously analyzing any possible case in which a great quantity of alarms are produced.

Area-Efficient Linear Regression Architecture for Real-Time Signal Processing on FPGAs

Linear regression is a technique widely used in digital signal processing. It consists on finding the linear function that better fits a given set of samples. This paper proposes different hardware architectures for the implementation of the linear regression method on FPGAs, specially targeting area restrictive systems. It saves area at the cost of constraining the lengths of the input signal to some fixed values. We have implemented the proposed scheme in an Automatic Modulation Classifier, meeting the hard real-time constraints this kind of systems have.

Optical signal processing with electrooptic modulators and dispersion

A review of the main techniques that have been proposed for temporal processing of optical pulses that are the counterpart of the well-known spatial arrangements will be presented. They are translated to the temporal domain via the space-time duality and implemented with electrooptical phase and amplitude modulators and dispersive devices. We will introduce new variations of the conventional approaches and we will focus on their application to optical communications systems

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.

Physical data acquisition and PWM signal generation using a microcontroller allowing control for DC motor rotation speed

El objetivo de este proyecto es diseñar un sistema capaz de controlar la velocidad de rotación de un motor DC en función del valor de temperatura obtenido de un sensor. Para ello se generará con un microcontrolador una señal PWM, cuyo ciclo de trabajo estará en función de la temperatura medida. En lo que respecta a la fase de diseño, hay dos partes claramente diferenciadas, relativas al hardware y al software. En cuanto al diseño del hardware puede hacerse a su vez una división en dos partes. En primer lugar, hubo que diseñar la circuitería necesaria para adaptar los niveles de tensión entregados por el sensor de temperatura a los niveles requeridos por ADC, requerido para digitalizar la información para su posterior procesamiento por parte del microcontrolador. Por tanto hubo que diseñar capaz de corregir el offset y la pendiente de la función tensión-temperatura del sensor, a fin de adaptarlo al rango de tensión requerido por el ADC. Por otro lado, hubo que diseñar el circuito encargado de controlar la velocidad de rotación del motor. Este circuito estará basado en un transistor MOSFET en conmutación, controlado mediante una señal PWM como se mencionó anteriormente. De esta manera, al variar el ciclo de trabajo de la señal PWM, variará de manera proporcional la tensión que cae en el motor, y por tanto su velocidad de rotación. En cuanto al diseño del software, se programó el microcontrolador para que generase una señal PWM en uno de sus pines en función del valor entregado por el ADC, a cuya entrada está conectada la tensión obtenida del circuito creado para adaptar la tensión generada por el sensor. Así mismo, se utiliza el microcontrolador para representar el valor de temperatura obtenido en una pantalla LCD. Para este proyecto se eligió una placa de desarrollo mbed, que incluye el microcontrolador integrado, debido a que facilita la tarea del prototipado. Posteriormente se procedió a la integración de ambas partes, y testeado del sistema para comprobar su correcto funcionamiento. Puesto que el resultado depende de la temperatura medida, fue necesario simular variaciones en ésta, para así comprobar los resultados obtenidos a distintas temperaturas. Para este propósito se empleó una bomba de aire caliente. Una vez comprobado el funcionamiento, como último paso se diseñó la placa de circuito impreso. Como conclusión, se consiguió desarrollar un sistema con un nivel de exactitud y precisión aceptable, en base a las limitaciones del sistema. SUMMARY: It is obvious that day by day people’s daily life depends more on technology and science. Tasks tend to be done automatically, making them simpler and as a result, user life is more comfortable. Every single task that can be controlled has an electronic system behind. In this project, a control system based on a microcontroller was designed for a fan, allowing it to go faster when temperature rises or slowing down as the environment gets colder. For this purpose, a microcontroller was programmed to generate a signal, to control the rotation speed of the fan depending on the data acquired from a temperature sensor. After testing the whole design developed in the laboratory, the next step taken was to build a prototype, which allows future improvements in the system that are discussed in the corresponding section of the thesis.

Signal to noise ratio maximization in quiet zone acquisitions for range assessment at sub-millimeter wavelengths

This paper proposes a quiet zone probing approach which deals with low dynamic range quiet zone acquisitions. Lack of dynamic range is a feature of millimeter and sub-millimeter wavelength technologies. It is consequence of the gradually smaller power generated by the instrumentation, that follows a f^α law with frequency, being α≥1 variable depending on the signal source’s technology. The proposed approach is based on an optimal data reduction scenario which redounds in a maximum signal to noise ratio increase for the signal pattern, with minimum information losses. After theoretical formulation, practical applications of the technique are proposed.

A new feature extraction method for signal classification applied to cat spinal cord signals

In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods.

Dissecting Arabidopsis Gß signal transduction on the protein surface.

The heterotrimeric G-protein complex provides signal amplification and target specificity. The Arabidopsis (Arabidopsis thaliana) G?-subunit of this complex (AGB1) interacts with and modulates the activity of target cytoplasmic proteins. This specificity resides in the structure of the interface between AGB1 and its targets. Important surface residues of AGB1, which were deduced from a comparative evolutionary approach, were mutated to dissect AGB1-dependent physiological functions. Analysis of the capacity of these mutants to complement well-established phenotypes of G?-null mutants revealed AGB1 residues critical for specific AGB1-mediated biological processes, including growth architecture, pathogen resistance, stomata-mediated leaf-air gas exchange, and possibly photosynthesis. These findings provide promising new avenues to direct the finely tuned engineering of crop yield and traits.