Force Sensor Characterization Under Sinusoidal Excitations

The aim in the current work is the development of a method to characterize force sensors under sinusoidal excitations using a primary standard as the source of traceability. During this work the influence factors have been studied and a method to minimise their contributions, as well as the corrections to be performed under dynamic conditions have been established. These results will allow the realization of an adequate characterization of force sensors under sinusoidal excitations, which will be essential for its further proper use under dynamic conditions. The traceability of the sensor characterization is based in the direct definition of force as mass multiplied by acceleration. To do so, the sensor is loaded with different calibrated loads and is maint ained under different sinusoidal accelerations by means of a vibration shaker system that is able to generate accelerations up to 100 m/s2 with frequencies from 5 Hz up to 2400 Hz. The acceleration is measured by means of a laser vibrometer with traceabili ty to the units of time and length. A multiple channel data acquisition system is also required to simultaneously acquire the electrical output signals of the involved instrument in real time.

Two Different Approaches of Feature Extraction for Classifying the EEG Signals

The electroencephalograph (EEG) signal is one of the most widely used signals in the biomedicine field due to its rich information about human tasks. This research study describes a new approach based on i) build reference models from a set of time series, based on the analysis of the events that they contain, is suitable for domains where the relevant information is concentrated in specific regions of the time series, known as events. In order to deal with events, each event is characterized by a set of attributes. ii) Discrete wavelet transform to the EEG data in order to extract temporal information in the form of changes in the frequency domain over time- that is they are able to extract non-stationary signals embedded in the noisy background of the human brain. The performance of the model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed scheme has potential in classifying the EEG signals.

Two Different Approaches of Feature Extraction for Classifying the EEG Signals

The focus of this chapter is to study feature extraction and pattern classification methods from two medical areas, Stabilometry and Electroencephalography (EEG). Stabilometry is the branch of medicine responsible for examining balance in human beings. Balance and dizziness disorders are probably two of the most common illnesses that physicians have to deal with. In Stabilometry, the key nuggets of information in a time series signal are concentrated within definite time periods are known as events. In this chapter, two feature extraction schemes have been developed to identify and characterise the events in Stabilometry and EEG signals. Based on these extracted features, an Adaptive Fuzzy Inference Neural network has been applied for classification of Stabilometry and EEG signals.

A Stress-Detection System Based on Physiological Signals and Fuzzy Logic

A stress-detection system is proposed based on physiological signals. Concretely, galvanic skin response (GSR) and heart rate (HR) are proposed to provide information on the state of mind of an individual, due to their nonintrusiveness and noninvasiveness. Furthermore, specific psychological experiments were designed to induce properly stress on individuals in order to acquire a database for training, validating, and testing the proposed system. Such system is based on fuzzy logic, and it described the behavior of an individual under stressing stimuli in terms of HR and GSR. The stress-detection accuracy obtained is 99.5% by acquiring HR and GSR during a period of 10 s, and what is more, rates over 90% of success are achieved by decreasing that acquisition period to 3-5 s. Finally, this paper comes up with a proposal that an accurate stress detection only requires two physiological signals, namely, HR and GSR, and the fact that the proposed stress-detection system is suitable for real-time applications.

Quantitative evaluation of artifact removal in real magnetoencephalogram signals with blind source separation

The magnetoencephalogram (MEG) is contaminated with undesired signals, which are called artifacts. Some of the most important ones are the cardiac and the ocular artifacts (CA and OA, respectively), and the power line noise (PLN). Blind source separation (BSS) has been used to reduce the influence of the artifacts in the data. There is a plethora of BSS-based artifact removal approaches, but few comparative analyses. In this study, MEG background activity from 26 subjects was processed with five widespread BSS (AMUSE, SOBI, JADE, extended Infomax, and FastICA) and one constrained BSS (cBSS) techniques. Then, the ability of several combinations of BSS algorithm, epoch length, and artifact detection metric to automatically reduce the CA, OA, and PLN were quantified with objective criteria. The results pinpointed to cBSS as a very suitable approach to remove the CA. Additionally, a combination of AMUSE or SOBI and artifact detection metrics based on entropy or power criteria decreased the OA. Finally, the PLN was reduced by means of a spectral metric. These findings confirm the utility of BSS to help in the artifact removal for MEG background activity.

Estimation of functional connectivity from electromagnetic signals and the amount of empirical data required

An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available. For event-related protocols, the amount of data also affects the temporal resolution of the analysis. We use analytical expressions to calculate the amount of empirical data needed to establish whether a certain level of dependency is significant when the time series are autocorrelated, as is the case for biological signals. These analytical results are then contrasted with estimates from simulations based on real data recorded with magnetoencephalography during a resting-state paradigm and during the presentation of visual stimuli. Results indicate that, for broadband signals, 50–100 s of data is required to detect a true underlying cross-correlations coefficient of 0.05. This corresponds to a resolution of a few hundred milliseconds for typical event-related recordings. The required time window increases for narrow band signals as frequency decreases. For instance, approximately 3 times as much data is necessary for signals in the alpha band. Important implications can be derived for the design and interpretation of experiments to characterize weak interactions, which are potentially important for brain processing.

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.

Analysis and design of multirate synchronous sampling schemes for sparse multiband signals

We consider the problem of developing efficient sampling schemes for multiband sparse signals. Previous results on multicoset sampling implementations that lead to universal sampling patterns (which guarantee perfect reconstruction), are based on a set of appropriate interleaved analog to digital converters, all of them operating at the same sampling frequency. In this paper we propose an alternative multirate synchronous implementation of multicoset codes, that is, all the analog to digital converters in the sampling scheme operate at different sampling frequencies, without need of introducing any delay. The interleaving is achieved through the usage of different rates, whose sum is significantly lower than the Nyquist rate of the multiband signal. To obtain universal patterns the sampling matrix is formulated and analyzed. Appropriate choices of the parameters, that is the block length and the sampling rates, are also proposed.

Design of universal multicoset sampling patterns for compressed sensing of multiband sparse signals

Many problems in digital communications involve wideband radio signals. As the most recent example, the impressive advances in Cognitive Radio systems make even more necessary the development of sampling schemes for wideband radio signals with spectral holes. This is equivalent to considering a sparse multiband signal in the framework of Compressive Sampling theory. Starting from previous results on multicoset sampling and recent advances in compressive sampling, we analyze the matrix involved in the corresponding reconstruction equation and define a new method for the design of universal multicoset codes, that is, codes guaranteeing perfect reconstruction of the sparse multiband signal.

Quantum optical signals in telecommunication networks

Introducción a una red óptica metropolitana cuántica donde señales cuánticas y convencionales son multiplexadas en longitud de onda utilizando bandas separadas del espectro óptico. El enrutado se realiza con componentes pasivos para no perturbar los qubits. Se estudian dos redes: red de acceso WDM-PON y red metropolitana completa con backbone DWDM y redes de acceso WDM-PON.

Signals and Systems Students trainer.

Higher education students demand fast feedback about their assignments and the opportunity to repeat them in case they do in a wrong way. Here a computer based trainer for Signals and Systems students is presented. An application, that automatically generates and assesses thousands of numerically different versions of several Signals and Systems problems have been developed. This applet guides the students to find the solution and automatically assesses and grades the students proposed solution. The students can use the application to practice in solving several types of Signals and Systems basic problems. After selecting the problem type, the student introduces a seed and the application generates a numerical version of the selected problem. Then the application presents a sequence of questions that the students must solve and the application automatically assess their answers. After solving a given problem, the students can repeat the same numerical variation of the problem by introducing the same seed to the application. In this way, they can review their solution with the help of the hints given by the application for wrong solutions. This application can also be used as an automatic assessment tool by the instructor. When the assessment is made in a controlled environment (examination classroom or laboratory) the instructor can use the same seed for all students. Otherwise, different seeds can be assigned to different students and in this way they solve different numerical variation of the proposed problem, so cheating becomes an arduous task. Given a problem type, the mathematical or conceptual difficulty of the problem can vary depending on the numerical values of the parameters of the problem. The application permits to easily select groups of seeds that yield to numerical variations with similar mathematical or conceptual difficulty. This represents an advantage over a randomised task assignment where students are asked to solve tasks with different difficulty.

Excitación y control de IGBTs de un inversor trifásico sinusoidal

El origen del proyecto se encuentra en la mejora de un inversor trifásico sinusoidal comercial sobre la base del estudio de las técnicas de excitación óptimas para los IGBTs que lo componen en su etapa de potencia. En las primeras fases de planteamiento del proyecto se propone una idea mucho más ambiciosa, la realización de un nuevo convertidor de emergencia, destinado al sector ferroviario, para dar servicio de climatización. Este convertidor está formado por la asociación en cascada de un bloque DC/DC elevador y un bloque inversor DC/AC trifásico controlado mediante PWM con modulación sinusoidal. Se pretendía así dar solución a las siguientes problemáticas detectadas en los convertidores comercializados hasta el momento: un bloque elevador excesivamente sobredimensionado, subsistemas de control independientes para los dos bloques que configuran el convertidor, adicionalmente, la tarjeta driver se rediseña con cada cambio de especificaciones por parte de un nuevo cliente y finalmente, las comunicaciones tanto de diagnosis como de mantenimiento necesitaban una importante actualización. Inicialmente, se ha realizado un estudio teórico de los bloques elevador e inversor para poder realizar el diseño y dimensionamiento de sus componentes tanto semiconductores como electromagnéticos. Una vez completada la parte de potencia, se estudia el control que se realiza mediante medidas directas y simulación tanto de la estrategia de control del elevador como del inversor. Así se obtiene una información completa de la funcionalidad de las tarjetas existentes. Se desea realizar el diseño de una única tarjeta controladora y una única tarjeta de drivers para ambos bloques. Por problemas ajenos, en el transcurso de este proyecto se cancela su realización comercial, con lo que se decide al menos crear la placa de control y poder gobernar un convertidor ya existente, sustituyendo la tarjeta de control del bloque elevador. Para poder fabricar la placa de control se divide en dos tarjetas que irán conectadas en modo sándwich. En una tarjeta está el microcontrolador y en otra está todo el interface necesario para operar con el sistema: entradas y salidas digitales, entradas y salidas analógicas, comunicación CAN, y un pequeño DC/DC comercial que proporciona alimentación al prototipo. Se realiza un pequeño programa funcional para poder manejar el convertidor, el cual con una tensión de 110V DC, proporciona a la salida una tensión de 380V AC. Como ya se ha expuesto, debido a la cancelación del proyecto industrial no se profundiza más en su mejora y se decide proponerlo para su evaluación en su fase actual. ABSTRACT. The beginning of the project is found in the improvement of a commercial sine wave three phase inverter which is based in a study about optimal excitation techniques to IGBTs which compose in the power stage. In the early phases of project it is proposed a much more ambitious idea, the fact of a new emergency converter, proposed for the rail sector to work in an air condition unit. This converter is formed by an association of a block cascaded DC/DC booster and a block DC/AC inverter three-phase controlled by a sine wave modulation PWM. The purposed was to give a solution to following problems detected in commercial converters nowadays: an excessively oversized block boost, independent control subsystems for two blocks that configure the converter. In addition, driver board is redesigned with each specifications change demand it a new customer, and finally, the communications, diagnostic and maintenance that needed a important upgrade. Initially, it has been performed a theoretical study of boost and the inverter blocks to be able to perform the component’s design and the size (semiconductor and electromagnetic fields). Once finished power study, it is analysed the control performed using direct measures and simulation of boost control strategy and inverter. With this it is obtained complete information about existing cards functionality. The project is looking for the design of just one controller card and one drivers´ card for both blocks. By unrelated problems, during the course of this project a commercial realization. So at least its decided to create control board to be able to existing converter, replacing boost block’s control board. To be able to manufacture control board it is divided in two cards connected in sandwiching mode. In a card is microcontroller and in another is all needed interface to operate with the system: digital inputs and outputs, analogical inputs and outputs, CAN communication, and a small DC / DC business that provide power supply to the prototype. It is performed a small functional program to handle the converter, which with an input voltage 110V DC provides an output voltage 380V AC. As already has been exposed, due to industrial project cancellation it is decided no to continue with all improvements and directly to evaluate it in the current phase.

Secure transmission of information by digital chaotic signals

Protecting signals is one of the main tasks in information transmission. A large number of different methods have been employed since many centuries ago. Most of them have been based on the use of certain signal added to the original one. When the composed signal is received, if the added signal is known, the initial information may be obtained. The main problem is the type of masking signal employed. One possibility is the use of chaotic signals, but they have a first strong limitation: the need to synchronize emitter and receiver. Optical communications systems, based on chaotic signals, have been proposed in a large number of papers. Moreover, because most of the communication systems are digital and conventional chaos generators are analogue, a conversion analogue-digital is needed. In this paper we will report a new system where the digital chaos is obtained from an optically programmable logic structure. This structure has been employed by the authors in optical computing and some previous results in chaotic signals have been reported. The main advantage of this new system is that an analogue-digital conversion is not needed. Previous works by the authors employed Self-Electrooptical Effect Devices but in this case more conventional structures, as semiconductor laser amplifiers, have been employed. The way to analyze the characteristics of digital chaotic signals will be reported as well as the method to synchronize the chaos generators located in the emitter and in the receiver.

Analysis of digital chaotic optical signals

The main objective of this paper is to present some tools to analyze a digital chaotic signal. We have proposed some of them previously, as a new type of phase diagrams with binary signals converted to hexadecimal. Moreover, the main emphasis will be given in this paper to an analysis of the chaotic signal based on the Lempel and Ziv method. This technique has been employed partly by us to a very short stream of data. In this paper we will extend this method to long trains of data (larger than 2000 bit units). The main characteristics of the chaotic signal are obtained with this method being possible to present numerical values to indicate the properties of the chaos.

Transmission of digital chaotic and information-bearing signals in optical communication systems

A new proposal to have secure communications in a system is reported. The basis is the use of a synchronized digital chaotic systems, sending the information signal added to an initial chaos. The received signal is analyzed by another chaos generator located at the receiver and, by a logic boolean function of the chaotic and the received signals, the original information is recovered. One of the most important facts of this system is that the bandwidth needed by the system remain the same with and without chaos.