Refined Kolmogorov complexity of analog, evolving and stochastic recurrent neural networks

Kolmogorov complexity measures the compressibility of real numbers. We provide a refined characterization of the hypercomputational power of analog, evolving, and stochastic neural networks based on the Kolmogorov complexity of their real weights, evolving weights, and real probabilities, respective...

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Vydané v:	Information sciences Ročník 711; s. 122104
Hlavní autori:	Cabessa, Jérémie, Strozecki, Yann
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Inc 01.09.2025
Predmet:	Analog computation Computability theory Computational power Echo state networks Kolmogorov complexity Quantization Recurrent neural networks Stochastic computation Recurrent neural networks Computability theory Computational power Echo state networks Kolmogorov complexity Quantization Analog computation Stochastic computation
ISSN:	0020-0255
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