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    Wyświetlanie 1-2 z 2
    Tytuł:
    Optimizing information processing in brain-inspired neural networks
    Autorzy:
    Paprocki, B.
    Pregowska, A.
    Szczepanski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/202095.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    neural network
    entropy
    mutual information
    noise
    inhibitory neuron
    Opis:
    The way brain networks maintain high transmission efficiency is believed to be fundamental in understanding brain activity. Brains consisting of more cells render information transmission more reliable and robust to noise. On the other hand, processing information in larger networks requires additional energy. Recent studies suggest that it is complexity, connectivity, and function diversity, rather than just size and the number of neurons, that could favour the evolution of memory, learning, and higher cognition. In this paper, we use Shannon information theory to address transmission efficiency quantitatively. We describe neural networks as communication channels, and then we measure information as mutual information between stimuli and network responses. We employ a probabilistic neuron model based on the approach proposed by Levy and Baxter, which comprises essential qualitative information transfer mechanisms. In this paper, we overview and discuss our previous quantitative results regarding brain-inspired networks, addressing their qualitative consequences in the context of broader literature. It is shown that mutual information is often maximized in a very noisy environment e.g., where only one-third of all input spikes are allowed to pass through noisy synapses and farther into the network. Moreover, we show that inhibitory connections as well as properly displaced long-range connections often significantly improve transmission efficiency. A deep understanding of brain processes in terms of advanced mathematical science plays an important role in the explanation of the nature of brain efficiency. Our results confirm that basic brain components that appear during the evolution process arise to optimise transmission performance.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2020, 68, 2; 225-233
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    On certain ‘tools’for research into the perception and creation of music and the complex ways in which they affect one another
    Autorzy:
    Humięcka-Jakubowska, Justyna
    Powiązania:
    https://bibliotekanauki.pl/articles/780287.pdf
    Data publikacji:
    2011
    Wydawca:
    Uniwersytet im. Adama Mickiewicza w Poznaniu
    Tematy:
    perception
    musical structure
    modelling
    entropy
    probability
    Markov process
    mutual information
    parse
    expectation
    surprise
    Opis:
    Perception is a constructive mental process, which cannot be considered impersonally. Similarly, music cannot be cognised solely on the basis of its score, since its coming into being is strictly connected to the activation of human memory and sound imagination. The patterns that emerge from the sounds of heard music enable the listener to draw conclusions regarding the structures those sounds embody. However, such conclusions are accompanied by a degree of uncertainty, which concerns not just the perceived moment of the heard music, but also the way in which it is represented in the listener’s memory. Perception is an inferential, multi-layered, uncertain process, in which particular patterns seem more likely than others. Mental representations of those probabilities lie behind such essential musical phenomena as surprise, tension, expectation and pitch identification, which are fixed elements of theperception of music. The aim of the present article is to describe the essence of three selected types of music modelling, based on spectral anticipation (Shlomo Dubnov), based on memory (Rens Bod), and exploiting the dynamic character of music to obtain information (Samer Abdallah and Mark Plumbley). All these models take account of the element of uncertainty that accompanies the perception of music; hence they make use the foundations of information theory and statistical analysis as measurement ‘tools’. The use of these tools makes it possible to obtain numerical rates, which inform us of the degree of predictability of the musical structures being analysed. One crucial advantage of these methods is the possibility of evaluating them in respect to the use of real musical structures, deriving from actual music, and not abstract structures formed for the purposes of research. We obtain cognitive insight into the analysed music by employing methods of a mathematical provenance, and so we have the possibility of examining music whilst taking account of the role of the listener, but with the use of objectivised methods.
    Źródło:
    Interdisciplinary Studies in Musicology; 2011, 10; 61-76
    1734-2406
    Pojawia się w:
    Interdisciplinary Studies in Musicology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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