2001
Authors
Oliveira, PM; Barroso, V;
Publication
ISSPA 2001: SIXTH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, VOLS 1 AND 2, PROCEEDINGS
Abstract
The concepts of Instantaneous Frequency (IFt) and Instantaneous Bandwidth (IBt) have traditionally been considered as independent spectral features. Recent work has suggested, however, that the spectral dynamics of the signal (and, hence, its IFt) may have an impact on IBt and on the achievable spectral resolution. In this article, we consider model based AR spectral estimators. Simulations are done with several distinct time-frequency tools, to confirm the theoretical predictions.
2000
Authors
Costa, P; Moreira, A; Sousa, A; Marques, P; Costa, P; Matos, A;
Publication
ROBOCUP-99: ROBOT SOCCER WORLD CUP III
Abstract
This paper describes the 5dpo team. The paper will be divided into three main sections, corresponding to three main blocks: the Global Level, the Local Level and the Interface Level. These Levels, their subsystems and some implementation details will be described next.
2000
Authors
Costa, P; Moreira, A; Sousa, A; Marques, P; Costa, P; Matos, A;
Publication
ROBOCUP-99: ROBOT SOCCER WORLD CUP III
Abstract
This paper describes the 5dpo-2000 team, The paper will be divided into three main sections, corresponding to three main blocks: the Global Level, the Local Level and the Interface Level. These Levels, their subsystems and some implementation details will be described next.
2000
Authors
Malheiro, B; Oliveira, E;
Publication
ADVANCES IN ARTIFICIAL INTELLIGENCE
Abstract
The ability to solve conflicting beliefs is crucial for multiagent systems where the information is dynamic, incomplete and distributed over a group of autonomous agents. The proposed distributed belief revision approach consists of a distributed truth maintenance system and a set of autonomous belief revision methodologies. The agents have partial views and, frequently, hold disparate beliefs which are automatically detected by system's reason maintenance mechanism. The nature of these conflicts is dynamic and requires adequate methodologies for conflict resolution. The two types of conflicting beliefs addressed in this paper are Context Dependent and Context Independent Conflicts which result, in the first case, from the assignment, by different agents, of opposite belief statuses to the same belief, and, in the latter case, from holding contradictory distinct beliefs. The belief revision methodology for solving Context Independent Conflicts is, basically, a selection process based on the assessment of the credibility of the opposing belief statuses. The belief revision methodology for solving Context Dependent Conflicts is, essentially, a search process for a consensual alternative based on a "next best" relaxation strategy.
2000
Authors
Oliveira, PM; Barroso, V;
Publication
OCEANS 2000 MTS/IEEE - WHERE MARINE SCIENCE AND TECHNOLOGY MEET, VOLS 1-3, CONFERENCE PROCEEDINGS
Abstract
The complexity of real-life transients, coupled with the incomplete (or absent) knowledge of their statistical structure or defining features has motivated the interest on the use of blind, data driven detection schemes. One such scheme, proposed by Jones and Sayeed, uses Time-Frequency distributions to implement sub-optimal quadratic detectors which, under certain conditions, approach the performance of optimal quadratic detectors. However, their use of Fisher's discriminants to obtain class separation has some drawbacks, which we solve by using a simple perceptron to obtain the discriminant. Also, more often than not, we will have a multiclass situation, implying the use of different Time-Frequency Distributions, each one of them tuned for a given class of transients. The different nature of these distributions (bias, type of cross-terms, time-frequency resolution, etc.) will hamper the performance of the algorithm, forcing the need for experimental validation of its heuristical aspects. These are the issues we will address. The algorithm will be applied to real data, and its performance investigated.
2000
Authors
Oliveira, PM; Barroso, V;
Publication
PROCEEDINGS OF THE TENTH IEEE WORKSHOP ON STATISTICAL SIGNAL AND ARRAY PROCESSING
Abstract
Is there a limit to the maximum resolution one can achieve when representing the signal's energy in the Time-Frequency plane? Some authors sustain that such a limit exists, and ignoring it is the cause of the known difficulties with some joint Time-Frequency distributions; others maintain that there is no such limit. In this article, we propose to analyze the merits and demerits of the several existing approaches, and suggest further arguments one might wish to consider. This will take us to the conclusion that, both from a tool-specific and from a general information-theoretic point of view, there is, indeed, a lower limit on the achievable resolution, even though the expression for that limit can not be given by the traditional Heisenberg-Gabor relations.
The access to the final selection minute is only available to applicants.
Please check the confirmation e-mail of your application to obtain the access code.