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    <title>A Synthesis of the Pribram Holonomic Theory of Vision With Quantum Associative Nets After Pre-Processing Using I.C.A. and Other Computational Models</title>
    <link>https://popups.uliege.be/3041-539x/index.php?id=1319</link>
    <description>Statistically-Independent Component Analysis (ICA) and sparseness-maximization net are models which maximally preserve information (&quot;infomax&quot;). Research of relevance of these algorithms for modeling image-processing in V1 is reported in comparison with the Holonomic Brain Theory by Pribram which advocates dendritic processing and its connection to quantum processing. &quot;Infomax&quot; models are presented and discussed as a possible early-processing gateway to higher visual processing involving quantum associative nets (Perus, 2000) and attractor dynamics. </description>
    <category domain="https://popups.uliege.be/3041-539x/index.php?id=65">Full text issues</category>
    <category domain="https://popups.uliege.be/3041-539x/index.php?id=83">Volume 10</category>
    <category domain="https://popups.uliege.be/3041-539x/index.php?id=960">Quantum Millennium, Quantum Universe, Quantum Worl...</category>
    <language>fr</language>
    <pubDate>Wed, 10 Jul 2024 10:53:14 +0200</pubDate>
    <lastBuildDate>Wed, 10 Jul 2024 10:53:23 +0200</lastBuildDate>
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