Search results for " Marko"
showing 10 items of 201 documents
El análisis cuantitativo de trayectorias laborales. Un estado del arte
2022
La metodología cuantitativa aplicada al estudio de las trayectorias laborales ha experimentado un rápido auge que se ha extendido más allá del tradicional análisis de secuencias. El presente artículo es un estado del arte del desarrollo de nuevas técnicas estadísticas que pueden aplicarse o ya se aplican al estudio de trayectorias laborales. Además, incluimos sugerencias de software estadístico para la aplicación de cada una de las técnicas descritas. A lo largo de todo el texto, podrá observarse que la descripción de cada técnica se ha realizado desde un punto de vista conceptual, con el objetivo de llegar a un público amplio, que no necesite poseer una fuerte formación estadística. Es med…
A Study of Perceptron Mapping Capability to Design Speech Event Detectors
2006
Event detection is a fundamental yet critical component in automatic speech recognition (ASR) systems that attempt to extract knowledge-based features at the front-end level. In this context, it is common practice to design the detectors inside well-known frameworks based on artificial neural network (ANN) or support vector machine (SVM). In the case of ANN, speech scientists often design their detector architecture relying on conventional feed-forward multi-layer perceptron (MLP) with sigmoidal activation function. The aim of this paper is to introduce other ANN architectures inside the context of detection-based ASR. In particular, a bank of feed-forward MLPs using sinusoidal activation f…
Textual data compression in computational biology: Algorithmic techniques
2012
Abstract In a recent review [R. Giancarlo, D. Scaturro, F. Utro, Textual data compression in computational biology: a synopsis, Bioinformatics 25 (2009) 1575–1586] the first systematic organization and presentation of the impact of textual data compression for the analysis of biological data has been given. Its main focus was on a systematic presentation of the key areas of bioinformatics and computational biology where compression has been used together with a technical presentation of how well-known notions from information theory have been adapted to successfully work on biological data. Rather surprisingly, the use of data compression is pervasive in computational biology. Starting from…
Dynamic Community Detection for Brain Functional Networks during Music Listening with Block Component Analysis
2023
Publisher Copyright: Author The human brain can be described as a complex network of functional connections between distinct regions, referred to as the brain functional network. Recent studies show that the functional network is a dynamic process and its community structure evolves with time during continuous task performance. Consequently, it is important for the understanding of the human brain to develop dynamic community detection techniques for such time-varying functional networks. Here, we propose a temporal clustering framework based on a set of network generative models and surprisingly it can be linked to Block Component Analysis to detect and track the latent community structure…
Channel Assembling with Priority-Based Queues in Cognitive Radio Networks: Strategies and Performance Evaluation
2014
[EN] With the implementation of channel assembling (CA) techniques, higher data rate can be achieved for secondary users in multi-channel cognitive radio networks. Recent studies which are based on loss systems show that maximal capacity can be achieved using dynamic CA strategies. However the channel allocation schemes suffer from high blocking and forced termination when primary users become active. In this paper, we propose to introduce queues for secondary users so that those flows that would otherwise be blocked or forcibly terminated could be buffered and possibly served later. More specifically, in a multi-channel network with heterogeneous traffic, two queues are separately allocate…
On the Performance of Channel Assembling and Fragmentation in Cognitive Radio Networks
2014
[EN] Flexible channel allocation may be applied to multi-channel cognitive radio networks (CRNs) through either channel assembling (CA) or channel fragmentation (CF). While CA allows one secondary user (SU) occupy multiple channels when primary users (PUs) are absent, CF provides finer granularity for channel occupancy by allocating a portion of one channel to an SU flow. In this paper, we investigate the impact of CF together with CA for SU flows by proposing a channel access strategy which activates both CF and CA and correspondingly evaluating its performance. In addition, we also consider a novel scenario where CA is enabled for PU flows. The performance evaluation is conducted based on…
Stochastic Stability Analysis for Markovian Jump Neutral Nonlinear Systems
2012
In this paper, the stability problem is studied for a class of Markovian jump neutral nonlinear systems with time-varying delay. By Lyapunov-Krasovskii function approach, a novel mean-square exponential stability criterion is derived for the situations that the system's transition rates are completely accessible, partially accessible and non-accessible, respectively. Moreover, the developed stability criterion is extended to the systems with different bounded sector nonlinear constraints. Finally, some numerical examples are provided to illustrate the effectiveness of the proposed methods.
Filtering design for two-dimensional Markovian jump systems with state-delays and deficient mode information
2014
This paper is concerned with the problem of H"~ filtering for a class of two-dimensional Markovian jump linear systems described by the Fornasini-Marchesini local state-space model. The systems under consideration are subject to state-delays and deficient mode information in the Markov chain. The description of deficient mode information is comprehensive that simultaneously includes the exactly known, partially unknown and uncertain transition probabilities. By invoking the properties of the transition probability matrix, together with the convexification of uncertain domains, a new H"~ performance analysis criterion for the filtering error system is firstly derived. Then, via some matrix i…
Convergence of Markov Chains
2020
We consider a Markov chain X with invariant distribution π and investigate conditions under which the distribution of X n converges to π as n→∞. Essentially it is necessary and sufficient that the state space of the chain cannot be decomposed into subspaces that the chain does not leave, or that are visited by the chain periodically; e.g., only for odd n or only for even n.
Creation and cognition for humanoid live dancing
2016
Abstract Computational creativity in dancing is a recent and challenging research field in Artificial Intelligence and Robotics. We present a cognitive architecture embodied in a humanoid robot capable to create and perform dances driven by the perception of music. The humanoid robot is able to suitably move, to react to human mate dancers and to generate novel and appropriate sequences of movements. The approach is based on a cognitive architecture that integrates Hidden Markov Models and Genetic Algorithms. The system has been implemented on a NAO robot and tested in public setting-up live performances, obtaining positive feedbacks from the audience.