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%).

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.

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.

The IST METRA Project

This article summarizes the main achievementsof the Multi-Element Transmit andReceive Antennas (METRA) Project, an ISTresearch and technological development project carried out between January 2000 and June 2001 by Universitat Politècnica de Catalunya, the Center for Personkommunikation of Aalborg University, Nokia Networks, Nokia Mobile Phones, and Vodafone Group Research and Development.The main objective of METRA was the performanceevaluation of multi-antenna terminals incombination with adaptive antennas at the basestation in UMTS communication systems. 1 AMIMO channel sounder was developed that providedrealistic multi-antenna channel measurements.Using these measured data, stochasticchannel models were developed and properly validated.These models were also evaluated inorder to estimate their corresponding channelcapacity. Different MIMO configurations andprocessing schemes were developed for both theFDD and TDD modes of UTRA, and their linkperformance was assessed. Performance evaluationwas completed by system simulations thatillustrated the benefits of MIMO configurationsto the network operator. Implementation cost vs.performance improvement was also covered bythe project, including the base station and terminalmanufacturer and network operator viewpoints.Finally, significant standards contributionswere generated by the project and presented to the pertinent 3GPP working groups.

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

Contribución al diseño de GNSS-SDR, un receptor GNSS de código abierto

[ANGLÈS] This project introduces GNSS-SDR, an open source Global Navigation Satellite System software-defined receiver. The lack of reconfigurability of current commercial-of-the-shelf receivers and the advent of new radionavigation signals and systems make software receivers an appealing approach to design new architectures and signal processing algorithms. With the aim of exploring the full potential of this forthcoming scenario with a plurality of new signal structures and frequency bands available for positioning, this paper describes the software architecture design and provides details about its implementation, targeting a multiband, multisystem GNSS receiver. The result is a testbed for GNSS signal processing that allows any kind of customization, including interchangeability of signal sources, signal processing algorithms, interoperability with other systems, output formats, and the offering of interfaces to all the intermediate signals, parameters and variables. The source code release under the GNU General Public License (GPL) secures practical usability, inspection, and continuous improvement by the research community, allowing the discussion based on tangible code and the analysis of results obtained with real signals. The source code is complemented by a development ecosystem, consisting of a website (http://gnss-sdr.org), as well as a revision control system, instructions for users and developers, and communication tools. The project shows in detail the design of the initial blocks of the Signal Processing Plane of the receiver: signal conditioner, the acquisition block and the receiver channel, the project also extends the functionality of the acquisition and tracking modules of the GNSS-SDR receiver to track the new Galileo E1 signals available. Each section provides a theoretical analysis, implementation details of each block and subsequent testing to confirm the calculations with both synthetically generated signals and with real signals from satellites in space.

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.

Mobile robot experimental modeling and control strategies using sensor fusion

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, and research 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. In this context the research developed includes the visual information as a meaningful source that allows detecting the obstacle position coordinates as well as planning the free obstacle trajectory that should be reached by the robot

Smart antennas in software radio base stations

The application of adaptive antenna techniques to fixed-architecture base stations has been shown to offer wide-ranging benefits, including interference rejection capabilities or increased coverage and spectral efficiency.Unfortunately, the actual implementation ofthese techniques to mobile communication scenarios has traditionally been set back by two fundamental reasons. On one hand, the lack of flexibility of current transceiver architectures does not allow for the introduction of advanced add-on functionalities. On the other hand, theoften oversimplified models for the spatiotemporal characteristics of the radio communications channel generally give rise toperformance predictions that are, in practice, too optimistic. The advent of software radio architectures represents a big step toward theintroduction of advanced receive/transmitcapabilities. Thanks to their inherent flexibilityand robustness, software radio architecturesare the appropriate enabling technology for theimplementation of array processing techniques.Moreover, given the exponential progression ofcommunication standards in coexistence andtheir constant evolution, software reconfigurabilitywill probably soon become the only costefficientalternative for the transceiverupgrade. This article analyzes the requirementsfor the introduction of software radio techniquesand array processing architectures inmultistandard scenarios. It basically summarizesthe conclusions and results obtained withinthe ACTS project SUNBEAM,1 proposingalgorithms and analyzing the feasibility ofimplementation of innovative and softwarereconfigurablearray processing architectures inmultistandard settings.

Smart antennas: state of the art

Aim of this contribution is to illustrate the state of the art of smart antenna research from several perspectives. The bow is drawn from transmitter issues via channel measurements and modeling, receiver signal processing, network aspects, technological challenges towards first smart antenna applications and current status of standardization. Moreover, some future prospects of different disciplines in smart antenna research are given.