Is complex signal processing for bone conduction hearing aids useful?

OBJECTIVES To establish whether complex signal processing is beneficial for users of bone anchored hearing aids. METHODS Review and analysis of two studies from our own group, each comparing a speech processor with basic digital signal processing (either Baha Divino or Baha Intenso) and a processor with complex digital signal processing (either Baha BP100 or Baha BP110 power). The main differences between basic and complex signal processing are the number of audiologist accessible frequency channels and the availability and complexity of the directional multi-microphone noise reduction and loudness compression systems. RESULTS Both studies show a small, statistically non-significant improvement of speech understanding in quiet with the complex digital signal processing. The average improvement for speech in noise is +0.9 dB, if speech and noise are emitted both from the front of the listener. If noise is emitted from the rear and speech from the front of the listener, the advantage of the devices with complex digital signal processing as opposed to those with basic signal processing increases, on average, to +3.2 dB (range +2.3 … +5.1 dB, p ≤ 0.0032). DISCUSSION Complex digital signal processing does indeed improve speech understanding, especially in noise coming from the rear. This finding has been supported by another study, which has been published recently by a different research group. CONCLUSIONS When compared to basic digital signal processing, complex digital signal processing can increase speech understanding of users of bone anchored hearing aids. The benefit is most significant for speech understanding in noise.

A Parallel Solver for the Time-Periodic Navier–Stokes Equations

We investigate parallel algorithms for the solution of the Navier–Stokes equations in space-time. For periodic solutions, the discretized problem can be written as a large non-linear system of equations. This system of equations is solved by a Newton iteration. The Newton correction is computed using a preconditioned GMRES solver. The parallel performance of the algorithm is illustrated.

Parallel and Distributed Data Management. Introduction

The manipulation and handling of an ever increasing volume of data by current data-intensive applications require novel techniques for e?cient data management. Despite recent advances in every aspect of data management (storage, access, querying, analysis, mining), future applications are expected to scale to even higher degrees, not only in terms of volumes of data handled but also in terms of users and resources, often making use of multiple, pre-existing autonomous, distributed or heterogeneous resources.

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.

A parallel implementation of 3D Zernike moment analysis

Zernike polynomials are a well known set of functions that find many applications in image or pattern characterization because they allow to construct shape descriptors that are invariant against translations, rotations or scale changes. The concepts behind them can be extended to higher dimension spaces, making them also fit to describe volumetric data. They have been less used than their properties might suggest due to their high computational cost. We present a parallel implementation of 3D Zernike moments analysis, written in C with CUDA extensions, which makes it practical to employ Zernike descriptors in interactive applications, yielding a performance of several frames per second in voxel datasets about 2003 in size. In our contribution, we describe the challenges of implementing 3D Zernike analysis in a general-purpose GPU. These include how to deal with numerical inaccuracies, due to the high precision demands of the algorithm, or how to deal with the high volume of input data so that it does not become a bottleneck for the system.

Descripción, comparación y ejemplos de uso de las funciones de la toolbox de procesado digital de imágenes de MATLAB®

Matlab, uno de los paquetes de software matemático más utilizados actualmente en el mundo de la docencia y de la investigación, dispone de entre sus muchas herramientas una específica para el procesado digital de imágenes. Esta toolbox de procesado digital de imágenes está formada por un conjunto de funciones adicionales que amplían la capacidad del entorno numérico de Matlab y permiten realizar un gran número de operaciones de procesado digital de imágenes directamente a través del programa principal. Sin embargo, pese a que MATLAB cuenta con un buen apartado de ayuda tanto online como dentro del propio programa principal, la bibliografía disponible en castellano es muy limitada y en el caso particular de la toolbox de procesado digital de imágenes es prácticamente nula y altamente especializada, lo que requiere que los usuarios tengan una sólida formación en matemáticas y en procesado digital de imágenes. Partiendo de una labor de análisis de todas las funciones y posibilidades disponibles en la herramienta del programa, el proyecto clasificará, resumirá y explicará cada una de ellas a nivel de usuario, definiendo todas las variables de entrada y salida posibles, describiendo las tareas más habituales en las que se emplea cada función, comparando resultados y proporcionando ejemplos aclaratorios que ayuden a entender su uso y aplicación. Además, se introducirá al lector en el uso general de Matlab explicando las operaciones esenciales del programa, y se aclararán los conceptos más avanzados de la toolbox para que no sea necesaria una extensa formación previa. De este modo, cualquier alumno o profesor que se quiera iniciar en el procesado digital de imágenes con Matlab dispondrá de un documento que le servirá tanto para consultar y entender el funcionamiento de cualquier función de la toolbox como para implementar las operaciones más recurrentes dentro del procesado digital de imágenes. Matlab, one of the most used numerical computing environments in the world of research and teaching, has among its many tools a specific one for digital image processing. This digital image processing toolbox consists of a set of additional functions that extend the power of the digital environment of Matlab and allow to execute a large number of operations of digital image processing directly through the main program. However, despite the fact that MATLAB has a good help section both online and within the main program, the available bibliography is very limited in Castilian and is negligible and highly specialized in the particular case of the image processing toolbox, being necessary a strong background in mathematics and digital image processing. Starting from an analysis of all the available functions and possibilities in the program tool, the document will classify, summarize and explain each function at user level, defining all input and output variables possible, describing common tasks in which each feature is used, comparing results and providing illustrative examples to help understand its use and application. In addition, the reader will be introduced in the general use of Matlab explaining the essential operations within the program and clarifying the most advanced concepts of the toolbox so that an extensive prior formation will not be necessary. Thus, any student or teacher who wants to start digital image processing with Matlab will have a document that will serve to check and understand the operation of any function of the toolbox and also to implement the most recurrent operations in digital image processing.

Flexible scheduling for non-deterministic, and-parallel execution of logic programs

Abstract is not available.

IDRA (IDeal Resource Allocation): Computing ideal speedups in parallel logic programming

We present a technique to estimate accurate speedups for parallel logic programs with relative independence from characteristics of a given implementation or underlying parallel hardware. The proposed technique is based on gathering accurate data describing one execution at run-time, which is fed to a simulator. Alternative schedulings are then simulated and estimates computed for the corresponding speedups. A tool implementing the aforementioned techniques is presented, and its predictions are compared to the performance of real systems, showing good correlation.

&ACE: A high-performance parallel prolog system

In recent years a lot of research has been invested in parallel processing of numerical applications. However, parallel processing of Symbolic and AI applications has received less attention. This paper presents a system for parallel symbolic computitig, narned ACE, based on the logic programming paradigm. ACE is a computational model for the full Prolog language, capable of exploiting Or-parall< lism and Independent And-parallelism. In this paper vve focus on the implementation of the and-parallel part of the ACE system (ralled &ACE) on a shared memory multiprocessor, d< scribing its organization, some optimizations, and presenting some performance figures, proving the abilhy of &ACE to efficiently exploit parallelism.

Memory performance of and-parallel prolog on shared-memory architectures

The goal of the RAP-WAM AND-parallel Prolog abstract architecture is to provide inference speeds significantly beyond those of sequential systems, while supporting Prolog semantics and preserving sequential performance and storage efficiency. This paper presents simulation results supporting these claims with special emphasis on memory performance on a two-level sharedmemory multiprocessor organization. Several solutions to the cache coherency problem are analyzed. It is shown that RAP-WAM offers good locality and storage efficiency and that it can effectively take advantage of broadcast caches. It is argued that speeds in excess of 2 ML IPS on real applications exhibiting medium parallelism can be attained with current technology.

B-LOG: A branch and bound methodology for the parallel execution of logic programs

We propose a computational methodology -"B-LOG"-, which offers the potential for an effective implementation of Logic Programming in a parallel computer. We also propose a weighting scheme to guide the search process through the graph and we apply the concepts of parallel "branch and bound" algorithms in order to perform a "best-first" search using an information theoretic bound. The concept of "session" is used to speed up the search process in a succession of similar queries. Within a session, we strongly modify the bounds in a local database, while bounds kept in a global database are weakly modified to provide a better initial condition for other sessions. We also propose an implementation scheme based on a database machine using "semantic paging", and the "B-LOG processor" based on a scoreboard driven controller.

Experimenting with independent and-parallel prolog using standard prolog

This paper presents an approximation to the study of parallel systems using sequential tools. The Independent And-parallelism in Prolog is an example of parallel processing paradigm in the framework of logic programming, and implementations like processing. But this potential can also be explored using only sequential systems. Being the spirit of this paper to show how this can be done with a standard system, only standard Prolog will be used in the implementations included. Such implementations include tests for parallelism in And-Prolog, a correctnesschecking meta-interpreter of

Experimenting with independent and-parallel prolog using standard prolog

This paper presents an approximation to the study of parallel systems using sequential tools. The Independent And-parallelism in Prolog is an example of parallel processing paradigm in the framework of logic programming, and implementations like processing. But this potential can also be explored using only sequential systems. Being the spirit of this paper to show how this can be done with a standard system, only standard Prolog will be used in the implementations included. Such implementations include tests for parallelism in And-Prolog, a correctnesschecking meta-interpreter of

Extraction of subjective properties in image processing

Most of the present digital images processing methods are related with objective characterization of external properties as shape, form or colour. This information concerns objective characteristics of different bodies and is applied to extract details to perform several different tasks. But in some occasions, some other type of information is needed. This is the case when the image processing system is going to be applied to some operation related with living bodies. In this case, some other type of object information may be useful. As a matter of fact, it may give additional knowledge about its subjective properties. Some of these properties are object symmetry, parallelism between lines and the feeling of size. These types of properties concerns more to internal sensations of living beings when they are related with their environment than to the objective information obtained by artificial systems. This paper presents an elemental system able to detect some of the above-mentioned parameters. A first mathematical model to analyze these situations is reported. This theoretical model will give the possibility to implement a simple working system. The basis of this system is the use of optical logic cells, previously employed in optical computing.

Digital Coherent Receivers and Advanced Optical Modulation Formats in 100 and 200 Gb/s DWDM Systems

Recent advances in coherent optical receivers is reviewed. Digital-Signal-Processing (DSP) based phase and polarization management techniques make coherent detection robust and feasible. With coherent detection, the complex field of the received optical signal is fully recovered, allowing compensation of linear and nonlinear optical impairments including chromatic dispersion (CD) and polarization-mode dispersion (PMD) using digital filters. Coherent detection and advanced optical modulation formats have become a key ingredient to the design of modern dense wavelength-division multiplexed (DWDM) optical broadband networks. In this paper, firstly we present the different subsystems of a digital coherent optical receiver, and secondly, we will compare the performance of some multi-level and multi-dimensional modulation formats in some physical impairments and in high spectral-efficiency (SE) and high-capacity DWDM transmissions, simulating the DSP with Matlab and the optical network performance with OptiSystem software.