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.

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.

Abstract
Ville's definition of Instantaneous Frequency (IF), even though widely used and accepted, fails in most cases of practical interest. This failure has been often reported, namely in the multicomponent case. In this paper, we will analyze the advantages and shortcomings of that definition, and determine when and why it fails, integrating all previously reported cases of failure in a simple unified theory. We will also be able to extrapolate and predict the behavior of the traditional definition for any type of multicomponent signal. Alternative definitions of IF are discussed.

Abstract
The nesting problem consists of defining the cutting plan of a piece of raw material in smaller irregular shapes, and has applications in the apparel and footwear industries. Due to its NP-hard nature, the optimal solution can only be guaranteed by exhaustively trying all possible solutions and choosing the best one. Because this is impractical in real-life industrial problems, automatic approaches are based on optimization meta-heuristics that search for sub-optimal but good enough solutions. These optimization techniques rely on the construction and evaluation of several solutions, thus requiring heavy geometric manipulation of the irregular polygons that constitute the problem data. Efficient processing of this geometric information is thus necessary to make effective fully automatic approaches to nesting problems in industrial environments. This paper describes Fafner, an FPGA-based custom computing machine that is used to accelerate the geometric operations, that are in the core of heuristic solutions to the nesting problem. The system is used as an auxiliary processor attached to a low cost personal computer, and combines a custom programmable processor with an array of custom circuits for the processing of irregular polygons.

Abstract
In this paper, we address the current developments of the "PISCIS" project. We focus on the experimental results from recent operational missions with an AUV in a estuarine environment. Besides describing mission planning and logistic details, we also present tools for oceanographic data processing and visualization. This will be demonstrated with some examples of collected data.

Abstract
A reliable navigation system is a key factor for the success of an operational mission with an AUV in a real scenario. In this paper, we address the main issues involved in the implementation of a long baseline (LBL) navigation system for a REMUS AUV. This system replaces both the original hardware and software of the vehicle with a simpler, faster, less expensive and more precise system, based on a Kalman filter. We also discuss the influence of transponder location in the overall performance of the LBL navigation, and present results obtained with this new system in operational missions.