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Since many signal processing problems can be posed as sample-based decision and estimation tasks, we discuss how studies from other fields such as neural networks might suggest improved architectures (models) and algorithms for these types of problems. We then concentrate on PAM equalization, showing that a reordering of the equivalent classification problem generates a ‘staircase’ which, while retaining...
Medical applications, such as medical diagnosis, can be understood as classification problems. While usual approaches try to minimize the number of errors, medical scenarios often require classifiers that face up with different types of costs. This paper analyzes the application of a particular class of Bregman divergences to design cost sensitive classifiers for medical applications. It has been...
For a Transmission System Power Operator such as Red Electrica de Espana (REE), operating a high power grid in real-time conditions, reliability of its communication circuits are a main concern. REE has developed a high availability communication networks with very low failure rates, its main design criteria being the physical diversity, i.e., the traffic between a given pair of nodes is routed by...
The transmission and reception of sensor measures between nodes in distributed target tracking applications of wireless sensor networks is energy expensive. This paper shows that a selective transmission policy can be used to increase the network lifetime without reducing the accuracy of the target parameter (position, velocity) estimates in a significant manner. To do so, nodes compute an importance...
Unpredictable topology changes, energy constraints and link unreliability make the information transmission a challenging problem in wireless sensor networks (WSN). Taking some ideas from machine learning methods, we propose a novel geographic routing algorithm for WSN, named Q-probabilistic routing (Q-PR), that makes intelligent routing decisions from the delayed reward of previous actions and the...
Energy is a valuable resource in wireless sensor networks since it constitutes a limiting factor for the network lifetime. In order to make an efficient use of its own energy resources, each node in the network should be aware of the energy resources at other nodes, which can be relevant to the success of their routing decisions. The proposal of this paper is twofold: (i) to design a routing algorithm...
A rate control (RC) algorithm for H.264 video coding with stored-B (SB) pictures is proposed for low-delay applications. Different models for P and SB pictures are defined for a better QP and MAD estimation. Furthermore, a novel saw-tooth shaped model of target buffer level has also been introduced for a proper bit allocation in GOP structures with SB pictures. Our experimental results show that this...
In this paper we propose an efficient energy-aware routing algorithm based on learning patterns. Energy and message importance are considered in a Bayesian model in order to establish intelligent decision rules that make the network economize in crucial resources.
In this paper we propose a new method for training classifiers for multi-class problems when classes are not (necessarily) mutually exclusive and may be related by means of a probabilistic tree structure. Our method is based on the definition of a Bayesian model relating network parameters, feature vectors and categories. Learning is stated as a maximum likelihood estimation problem of the classifier...
The paper is presenting a core idea of the research line, dedicated to tools and utilities for a more friendly information access. In order to make future multimedia systems smarter, new mechanisms for high-level data and user understanding need to be embedded in multimedia communication systems
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