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La ricerca find articoli where authors phrase all words ' Deco, G' sort by level,fasc_key/DESCEND, pagina_ini_num/ASCEND ha restituito 44 riferimenti
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    1. Deco, G; Zihl, J
      Top-down selective visual attention: A neurodynamical approach

      VISUAL COGNITION
    2. Silipo, R; Deco, G; Schurmann, B; Vergassola, R; Gremigni, C
      Investigating the underlying Markovian dynamics of ECG rhythms by information flow

      CHAOS SOLITONS & FRACTALS
    3. Deco, G; Zihl, J
      A neurodynamical model of visual attention: Feedback enhancement of spatial resolution in a hierarchical system

      JOURNAL OF COMPUTATIONAL NEUROSCIENCE
    4. Storck, J; Jakel, F; Deco, G
      Learning spatio-temporal stimuli with networks of spiking neurons and dynamic synapses

      NEUROCOMPUTING
    5. Corchs, S; Deco, G
      Selective attention in visual search: A neural network of phase oscillators

      NEUROCOMPUTING
    6. Corchs, S; Deco, G
      A neurodynamical model for selective visual attention using oscillators

      NEURAL NETWORKS
    7. Storck, J; Jakel, F; Deco, G
      Temporal clustering with spiking neurons and dynamic synapses: towards technological applications

      NEURAL NETWORKS
    8. Deco, G; Zihl, J
      Neurodynamical mechanism of binding and selective attention for visual search

      NEUROCOMPUTING
    9. Martignon, L; Deco, G; Laskey, K; Diamond, M; Freiwald, W; Vaadia, E
      Neural coding: Higher-order temporal patterns in the neurostatistics of cell assemblies

      NEURAL COMPUTATION
    10. Deco, G; Schurmann, B
      A neuro-cognitive visual system for object recognition based on testing ofinteractive attentional top-down hypotheses

      PERCEPTION
    11. Deco, G; Schurmann, B
      A hierarchical neural system with attentional top-down enhancement of the spatial resolution for object recognition

      VISION RESEARCH
    12. Silipo, R; Deco, G; Bartsch, H
      Rest EEG hidden dynamics as a discriminant for brain tumour classification

      ARTIFICIAL NEURAL NETWORKS IN BIOMEDICINE
    13. Deco, G; Schurmann, B
      Spatiotemporal coding in the cortex: Information flow-based learning in spiking neural networks

      NEURAL COMPUTATION
    14. Silipo, R; Deco, G; Vergassola, R; Gremigni, C
      A characterization of HRV's nonlinear hidden dynamics by means of Markov models

      IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
    15. DECO G; SCHURMANN B
      THE CODING OF INFORMATION BY SPIKING NEURONS - AN ANALYTICAL STUDY

      Network
    16. OBRADOVIC D; DECO G
      INFORMATION MAXIMIZATION AND INDEPENDENT COMPONENT ANALYSIS - IS THERE A DIFFERENCE

      Neural computation
    17. SILIPO R; DECO G; VERGASSOLA R; BARTSCH H
      DYNAMICS EXTRACTION IN MULTIVARIATE BIOMEDICAL TIME-SERIES

      Biological cybernetics
    18. DECO G; SCHURMANN B
      STOCHASTIC RESONANCE IN THE MUTUAL INFORMATION BETWEEN INPUT AND OUTPUT SPIKE TRAINS OF NOISY CENTRAL NEURONS

      Physica. D
    19. DECO G; PARRA L
      NONLINEAR FEATURE-EXTRACTION BY REDUNDANCY REDUCTION IN AN UNSUPERVISED STOCHASTIC NEURAL-NETWORK

      Neural networks
    20. DECO G; NEUNEIER R; SCHURMANN B
      NONPARAMETRIC DATA SELECTION FOR NEURAL LEARNING IN NONSTATIONARY TIME-SERIES

      Neural networks
    21. SCHITTENKOPF C; DECO G; BRAUER W
      2 STRATEGIES TO AVOID OVERFITTING IN FEEDFORWARD NETWORKS

      Neural networks
    22. SCHITTENKOPF C; DECO G
      IDENTIFICATION OF DETERMINISTIC CHAOS BY AN INFORMATION-THEORETIC MEASURE OF THE SENSITIVE DEPENDENCE ON THE INITIAL CONDITIONS

      Physica. D
    23. STORCK J; DECO G
      NONLINEAR INDEPENDENT COMPONENT ANALYSIS AND MULTIVARIATE TIME-SERIESANALYSIS

      Physica. D
    24. SCHITTENKOPF C; DECO G
      TESTING NONLINEAR MARKOVIAN HYPOTHESES IN DYNAMICAL-SYSTEMS

      Physica. D
    25. DECO G; SCHURMANN B
      INFORMATION-TRANSMISSION AND TEMPORAL CODE IN CENTRAL SPIKING NEURONS

      Physical review letters
    26. DECO G; SCHITTENKOPF C; SCHURMANN B
      DETERMINING THE INFORMATION-FLOW OF DYNAMICAL-SYSTEMS FROM CONTINUOUSPROBABILITY-DISTRIBUTIONS

      Physical review letters
    27. SCHITTENKOPF C; DECO G; BRAUER W
      FINITE AUTOMATA-MODELS FOR THE INVESTIGATION OF DYNAMICAL-SYSTEMS

      Information processing letters
    28. OBRADOVIC D; DECO G
      AN INFORMATION-THEORY BASED LEARNING-PARADIGM FOR LINEAR FEATURE-EXTRACTION

      Neurocomputing
    29. PARRA L; DECO G; MIESBACH S
      STATISTICAL INDEPENDENCE AND NOVELTY DETECTION WITH INFORMATION PRESERVING NONLINEAR MAPS

      Neural computation
    30. SCHITTENKOPF C; DECO G
      EXPLORING THE INTRINSIC INFORMATION LOSS IN SINGLE-HUMPED MAPS BY REFINING MULTISYMBOL PARTITIONS

      Physica. D
    31. DECO G; SCHURMANN B
      STATISTICAL-ENSEMBLE THEORY OF REDUNDANCY REDUCTION AND THE DUALITY BETWEEN UNSUPERVISED AND SUPERVISED NEURAL LEARNING

      Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
    32. HAFT M; SCHLANG M; DECO G
      INFORMATION-THEORY AND LOCAL LEARNING RULES IN A SELF-ORGANIZING NETWORK OF ISING SPINS

      Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
    33. DECO G; OBRADOVIC D
      STATISTICAL PHYSICS THEORY OF QUERY LEARNING BY AN ENSEMBLE OF HIGHER-ORDER NEURAL NETWORKS

      Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
    34. DECO G; SCHURMANN B
      LEARNING TIME-SERIES EVOLUTION BY UNSUPERVISED EXTRACTION OF CORRELATIONS

      Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
    35. DECO G; PARRA L
      UNSUPERVISED LEARNING FOR BOLTZMANN MACHINES

      Network
    36. PARRA L; DECO G; MIESBACH S
      REDUNDANCY REDUCTION WITH INFORMATION-PRESERVING NONLINEAR MAPS

      Network
    37. DECO G; OBRADOVIC D
      DECORRELATED HEBBIAN LEARNING FOR CLUSTERING AND FUNCTION APPROXIMATION

      Neural computation
    38. DECO G; FINNOFF W; ZIMMERMANN HG
      UNSUPERVISED MUTUAL INFORMATION CRITERION FOR ELIMINATION OF OVERTRAINING IN SUPERVISED MULTILAYER NETWORKS

      Neural computation
    39. DECO G; OBRADOVIC D
      LINEAR REDUNDANCY REDUCTION LEARNING

      Neural networks
    40. DECO G; BRAUER W
      NONLINEAR HIGHER-ORDER STATISTICAL DECORRELATION BY VOLUME-CONSERVINGNEURAL ARCHITECTURES

      Neural networks
    41. PARRA L; DECO G
      CONTINUOUS BOLTZMANN MACHINE WITH ROTOR NEURONS

      Neural networks
    42. DECO G; MAIDAGAN J; FOJON O; RIVAROLA R
      DO SYMMETRICAL EIKONAL AND CONTINUUM DISTORTED-WAVE MODELS SATISFY THE CORRECT BOUNDARY-CONDITIONS

      Physica scripta. T
    43. DECO G; SCHURMANN B
      NEURAL LEARNING OF CHAOTIC SYSTEM BEHAVIOR

      IEICE transactions on fundamentals of electronics, communications and computer science
    44. DECO G; FOJON O; MAIDAGAN J; RIVAROLA R
      MATRIX CONTINUUM DISTORTED-WAVE APPROXIMATION FOR ELECTRON-CAPTURE

      Physical review. A


ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 10/08/20 alle ore 08:47:51