Enzo Mumolo

Adaptive predictive coding of speech by means of volterra predictors

In this paper a waveform coder configuration based on non linear adaptive prediction will be described. The coder is based on the characteristic of Volterra predictors to model non linear phenomena and to gather informations about the periodicity of the signal via high order statistical moments. The main result is that, by using this type of predictor, lower variance error signals can be obtained, as compared to the classical, linear, case.

On the stability of discrete time recursive Volterra filters

Many real nonlinear systems are characterized by an infinite input signal memory. In such conditions, system modeling by means of recursive polynomial filters requires a much lower number of coefficients with respect to nonrecursive realizations. However, the main problem of recursive polynomial filters is their inherent instability. This letter describes simple sufficient stability conditions for a class of discrete-time nonlinear systems based on recursive Volterra filters of arbitrary orders.

A stability condition for adaptive recursive second-order polynomial filters

Abstract Recursive polynomial filters require a much lower number of coefficients with respect to nonrecursive realizations. However, the main problem of recursive polynomial filters is their inherent instability. In this paper sufficient stability conditions for recursive quadratic polynomial filters are reported. Moreover, an application to nonlinear system identification is described.

V-vector algebra and its application to Volterra-adaptive filtering

In this paper, we describe a new algebraic structure called V-vector algebra, which is a formal basis for the development of Volterra-adaptive filter algorithms as an extension of linear-adaptive techniques. In this way, fast and numerically stable adaptive Volterra filtering algorithms can be easily derived from the known linear theory. V-vector algebra can also be applied to deal with linear multichannel filters with channels of different memory lengths. A reformulation of the Lee-Mathews fast recursive least squares (RLS) algorithm and a new fast and stable Givens rotation-based square root RLS algorithm, both derived using V-vector algebra, are finally presented.

Algorithms and architectures for acoustic localization based on microphone array in service robotics

This paper describes an experimental mobile robot with acoustic source localization capabilities for surveillance and transportation tasks in indoor environments. The location of a speaking operator is detected via a microphone array based algorithm; localization information are passed to a navigation module which sets up a navigation mission using knowledge of the environment map. The system has been developed using a distributed architecture with TCP/IP message passing. We describe the hardware and software architectures, as well as the algorithms. Experimental results describing the system performance in localization tasks are reported.

Fast Genetic Scan Matching Using Corresponding Point Measurements in Mobile Robotics

In this paper we address the problem of aligning two partially overlapping surfaces represented by points obtained in subsequent 2D scans for mobile robot pose estimation. The measured points representation contains incomplete measurements. We solve this problem by minimizing an alignment error via a genetic algorithm. Moreover, we propose an alignment metric based on a look-up table built during the first scan. Experimental results related to the convergence of the proposed algorithm are reported. We compare our approach with other scan matching algorithms proposed in the literature, and we show that our approach is faster and more accurate than the others.

An algorithm for the automatic differentiation between the speech of normals and patients with Friedreich's ataxia based on the short-time fractal dimension

In this paper, we describe an algorithm, based on acoustic pattern matching techniques, for providing an automatic, highly reliable distinction between normal and some kind of pathological speech (Friedreichs ataxia disease). For each utterance, the short-time fractal dimension parameter and, for comparison, the zero-crossing and energy ratio parameters are evaluated and used in the classification task by means of a dynamic programming procedure. Although all the parameters are able to differentiate the two groups, the fractal dimension parameter seems to provide a more reliable pattern classification than zero-crossing and energy ratio. Finally, we point out that, to the discrimination purpose, an accurate choice of the utterances to be pronounced by the subjects is to be considered.

SPATIAL MAP BUILDING USING FAST TEXTURE ANALYSIS OF ROTATING SONAR SENSOR DATA FOR MOBILE ROBOTS

This paper presents a novel, fast algorithm for accurate detection of the shape of targets around a mobile robot using a single rotating sonar element. The rotating sonar yields an image built up by the reflections of an ultrasonic beam directed at different scan angles. The image is then interpreted with an image-understanding approach based on texture analysis. Several important tasks are performed in this way, such as noise removal, echo correction and restoration. All these processes are obtained by estimating and restoring the degree of texture continuity. Texture analysis, in fact, allows us to look at the image on a large scale thus giving the possibility to infer the overall behavior of the reflection process. The algorithm has been integrated in a mobile robot. However, the algorithm is not suitable for working during the mobile robot movement, rather it can be used during the period when the robot stays in a fixed position.

A Hard Real-Time Kernel for Motorola Microcontrollers

This paper describes a real-time kernel for running embedded applications on a recent family of Motorola microcontrollers. Both periodic and aperiodic real-time tasks are managed, as well as non real-time tasks. The kernel has been called Yartos, and uses a hard real-time scheduling algorithm based on an EDF approach for the periodic task; aperiodic tasks are executed with a Total Bandwith Server.

Fast square-root RLS adaptive filtering algorithms

Abstract In this paper two fast RLS adaptive filtering algorithms are described. Both algorithms compute the lattice coefficients and are based on the development of square-root factorizations of the autocorrelation matrix. Due to the square-root nature of the algorithms, the recursion is numerically stable. Experimental evaluations have been performed in limited precision environment, and comparison with the stabilized fast transversal filter algorithm (Slock and Kailath, 1991) has been made. Since the described algorithms require O( N ) operations per sample, where N is the filter order, from a computational complexity point of view they represent a substantial advantage over the O( N 2 ) complexity of classical square-root algorithms.