Connections between signal processing and complex analysis

We describe one of the research lines of the Grup de Teoria de Funcions de la UAB UB, which deals with sampling and interpolation problems in signal analysis and their connections with complex function theory.

A knowledge based signal processing approach to tonic identification in indian classical music

In this paper, we describe several techniques for detecting tonic pitch value in Indian classical music. In Indian music, the raga is the basic melodic framework and it is built on the tonic. Tonic detection is therefore fundamental for any melodic analysis in Indian classical music. This workexplores detection of tonic by processing the pitch histograms of Indian classic music. Processing of pitch histograms using group delay functions and its ability to amplify certain traits of Indian music in the pitch histogram, is discussed. Three different strategies to detect tonic, namely, the concert method, the template matching and segmented histogram method are proposed. The concert method exploits the fact that the tonic is constant over a piece/concert.templatematchingmethod and segmented histogrammethodsuse the properties: (i) the tonic is always present in the background, (ii) some notes are less inflected and dominant, to detect the tonic of individual pieces. All the three methods yield good results for Carnatic music (90−100% accuracy), while for Hindustanimusic, the templatemethod works best, provided the v¯adi samv¯adi notes for a given piece are known (85%).

A Fast Gradient Approximation for Nonlinear Blind Signal Processing

When dealing with nonlinear blind processing algorithms (deconvolution or post-nonlinear source separation), complex mathematical estimations must be done giving as a result very slow algorithms. This is the case, for example, in speech processing, spike signals deconvolution or microarray data analysis. In this paper, we propose a simple method to reduce computational time for the inversion of Wiener systems or the separation of post-nonlinear mixtures, by using a linear approximation in a minimum mutual information algorithm. Simulation results demonstrate that linear spline interpolation is fast and accurate, obtaining very good results (similar to those obtained without approximation) while computational time is dramatically decreased. On the other hand, cubic spline interpolation also obtains similar good results, but due to its intrinsic complexity, the global algorithm is much more slow and hence not useful for our purpose.

Statistical reference criteria for adaptive signal processing in digital communications

A general criterion for the design of adaptive systemsin digital communications called the statistical reference criterionis proposed. The criterion is based on imposition of the probabilitydensity function of the signal of interest at the outputof the adaptive system, with its application to the scenario ofhighly powerful interferers being the main focus of this paper.The knowledge of the pdf of the wanted signal is used as adiscriminator between signals so that interferers with differingdistributions are rejected by the algorithm. Its performance isstudied over a range of scenarios. Equations for gradient-basedcoefficient updates are derived, and the relationship with otherexisting algorithms like the minimum variance and the Wienercriterion are examined.

Alternative Techniques of Neural Signal Processing in Neuroengineering

Neural signal processing is a discipline within neuroengineering. This interdisciplinary approach combines principles from machine learning, signal processing theory, and computational neuroscience applied to problems in basic and clinical neuroscience. The ultimate goal of neuroengineering is a technological revolution, where machines would interact in real time with the brain. Machines and brains could interface, enabling normal function in cases of injury or disease, brain monitoring, and/or medical rehabilitation of brain disorders. Much current research in neuroengineering is focused on understanding the coding and processing of information in the sensory and motor systems, quantifying how this processing is altered in the pathological state, and how it can be manipulated through interactions with artificial devices including brain–computer interfaces and neuroprosthetics.

Microinductive signal conditioning with resonant differential filters: high-sensitivity biodetection applications

Inductive-based devices integrated with Si technology for biodetection applications are characterized, using simple resonant differential filter configurations. This has allowed the corroboration of the viability of the proposed circuits, which are characterized by their very high simplicity, for microinductive signal conditioning in high-sensitivity sensor devices. The simulation of these simple circuits predicts sensitivities of the differential output voltage which can achieve values in the range of 0.1-1 V/nH, depending on the coil parameters. These very high-sensitivity values open the possibility for the experimental detection of extremely small inductance changes in the devices. For real microinductive devices, both series resistance and parasitic capacitive components contribute to the decrease of the differential circuit sensitivity. Nevertheless, measurements performed using micro-coils fabricated with relatively high series resistance and coupling parasitic effects have allowed detection of changes in the range of 2 nH. which are compatible with biodetection applications with estimated detection limits below the picomolarity range.

Drift compensation of gas sensor array data by Orthogonal Signal Correction

Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period.

Wigner higher-order spectra: definition, properties, computation and application to transient signal analysis

The Wigner higher order moment spectra (WHOS)are defined as extensions of the Wigner-Ville distribution (WD)to higher order moment spectra domains. A general class oftime-frequency higher order moment spectra is also defined interms of arbitrary higher order moments of the signal as generalizations of the Cohen’s general class of time-frequency representations. The properties of the general class of time-frequency higher order moment spectra can be related to theproperties of WHOS which are, in fact, extensions of the properties of the WD. Discrete time and frequency Wigner higherorder moment spectra (DTF-WHOS) distributions are introduced for signal processing applications and are shown to beimplemented with two FFT-based algorithms. One applicationis presented where the Wigner bispectrum (WB), which is aWHOS in the third-order moment domain, is utilized for thedetection of transient signals embedded in noise. The WB iscompared with the WD in terms of simulation examples andanalysis of real sonar data. It is shown that better detectionschemes can be derived, in low signal-to-noise ratio, when theWB is applied.

Population ageing and ICT: An exploratory review of technology innovation trough digital applications

The multidimensional process of physical, psychological, and social change produced by population ageing affects not only the quality of life of elderly people but also of our societies. Some dimensions of population ageing grow and expand over time (e.g. knowledge of the world events, or experience in particular situations), while others decline (e.g. reaction time, physical and psychological strength, or other functional abilities like reduced speed and tiredness). Information and Communication Technologies (ICTs) can help elderly to overcome possible limitations due to ageing. As a particular case, biometrics can allow the development of new algorithms for early detection of cognitive impairments, by processing continuous speech, handwriting or other challenged abilities. Among all possibilities, digital applications (Apps) for mobile phones or tablets can allow the dissemination of such tools. In this article, after presenting and discussing the process of population ageing and its social implications, we explore how ICTs through different Apps can lead to new solutions for facing this major demographic challenge.

Estudi sobre equalització electrònica per a sistemes de comunicació per fibra òptica

Estudi realitzat a partir d’una estada a Bell Labs (Lucent Technologies), New Jersey (Estats Units), entre el 15 de setembre de 2005 i el 15 de gener de 2006. Els sistemes de transmissió per fibra òptica fonamenten les principals xarxes de comunicacions. A mesura que la demanda d’ample de banda per usuari creixi, seran necessaris nous sistemes que siguin capaços de cobrir les necessitats a curt i llarg termini. La tecnologia dels sistemes òptics limita fortament la complexitat dels sistemes de transmissió / recepció en comparació, per exemple, als sistemes d’ones de ràdio. La tendència és la de dissenyar sistemes avançats amb detecció directa i mirar d’aplicar tècniques bàsiques de processat del senyal. Una d’aquestes tècniques és l’equalització electrònica, és a dir, fer ús de les tècniques de processament del senyal per tal de compensar la distorsió introduïda pel canal, deguda per una o diverses degradacions típiques: dispersió cromàtica, efectes no lineals, dispersió del mode de polarització (PMD) ... Dins d’un entorn comercial d’empresa, s’ha avaluat el funcionament dels sistemes d’equalització FFE-DFE aixi com MLSE en presència de dispersió cromàtica i/o dispersió del mode de polarització (PMD) en transmissions NRZ/RZ.

Experimentació amb un receptor software GPS-Galileo d'alta sensibilitat per a entorns interiors

Este proyecto se centra en el análisis de señales GPS, utilizando un receptor software desarrollado con Matlab en un proyecto de investigación para la Agencia Espacial Europea (ESA), llevado a cabo por parte del departamento de Telecomunicaciones e Ingeniería de Sistemas de la ETSE. Este software utiliza técnicas de procesado de señal de alta sensibilidad (HS-GNSS) que permite al usuario determinar su posición en entornos de difícil propagación como puede ser el caso de los escenarios interiores. Los datos experimentales se analizan en función del nivel de multipath que afecta a la señal de cada uno de los satélites, y la degradación que los escenarios interiores provocan en las señales, a causa del mobiliario, paredes, personas, etc. Para analizar los datos experimentales, se ha utilizado una métrica presentada en el congreso internacional EuCAP 2009, con la que es posible caracterizar las señales en función del nivel de multipath.

Experimental Modeling and Control Strategies on an Open Mobile Robot Platform PRIM

This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system

Abstracting qualitative information for process supervision

Supervisory systems evolution makes the obtaining of significant information from processes more important in the way that the supervision systems' particular tasks are simplified. So, having signal treatment tools capable of obtaining elaborate information from the process data is important. In this paper, a tool that obtains qualitative data about the trends and oscillation of signals is presented. An application of this tool is presented as well. In this case, the tool, implemented in a computer-aided control systems design (CACSD) environment, is used in order to give to an expert system for fault detection in a laboratory plant

Wall motion estimation in intracranial aneurysms

The quantification of wall motion in cerebral aneurysms is becoming important owing to its potential connection to rupture, and as a way to incorporate the effects of vascular compliance in computational fluid dynamics (CFD) simulations.Most of papers report values obtained with experimental phantoms, simulated images, or animal models, but the information for real patients is limited. In this paper, we have combined non-rigid registration (IR) with signal processing techniques to measure pulsation in real patients from high frame rate digital subtraction angiography (DSA). We have obtained physiological meaningful waveforms with amplitudes in therange 0mm-0.3mm for a population of 18 patients including ruptured and unruptured aneurysms. Statistically significant differences in pulsation were found according to the rupture status, in agreement with differences in biomechanical properties reported in the literature.