Application of Koniocortex-Like Networks to Cardiac Arrhythmias Classification

Torres-Alegre, Santiago; Benchaib, Yasmine; Vicente, José Manuel Ferrández; Andina, Diego

doi:10.1007/978-3-030-19651-6_26

Cited by 2 publications

(3 citation statements)

References 23 publications

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“…The application was a complex one: the classification of the WBCD Breast Cancer Database. Similar results were also achieved for completely different applications: business data in [26,27] and for cardiac arrhythmia classification in [28].…”

Section: Lateral Inhibitionsupporting

confidence: 76%

Competitive Perceptrons: The Relevance of Modeling New Bioinspired Properties Such as Intrinsic Plasticity, Metaplasticity, and Lateral Inhibition of Rate-Coding Artificial Neurons

Andina

2023

Biomimetics

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This article supports the relevance of modeling new bioinspired properties in rate-coding artificial neurons, focusing on fundamental neural properties rarely implemented thus far in artificial neurons, such as intrinsic plasticity, the metaplasticity of synaptic strength, and the lateral inhibition of neighborhood neurons. All these properties are bioinspired through empirical models developed by neurologists, and this in turn contributes to taking perceptrons to a higher potential level. Metaplasticity and intrinsic plasticity are different levels of plasticity and are believed by neurologists to have fundamental roles in memory and learning and therefore in the performance of neurons. Assuming that information about stimuli is contained in the firing rate of the connections among biological neurons, several models of artificial implementation have been tested. Analyzing their results and comparing them with learning and performance of state-of-the-art models, relevant advances are made in the context of the developing Industrial Revolution 4.0 based on advances in Machine Learning, and they may even initiate a new generation of artificial neural networks. As an example, a single-layer perceptron that includes the proposed advances is successfully trained to perform the XOR function, called the Competitive Perceptron, which is a new bioinspired artificial neuronal model with the potential of non-linear separability, continuous learning, and scalability, which is suitable to build efficient Deep Networks, overcoming the basic limitations of traditional perceptrons that have challenged scientists for half a century.

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Section: Lateral Inhibitionsupporting

confidence: 76%

Competitive Perceptrons: The Relevance of Modeling New Bioinspired Properties Such as Intrinsic Plasticity, Metaplasticity, and Lateral Inhibition of Rate-Coding Artificial Neurons

Andina

2023

Biomimetics

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“…Finally, the Koniocortex Like Network (KLN) [90] is a novel Bioinspired Artificial Neural Network that models relevant biological properties of neurons as Synaptic Directionality, Long Term Potenciation, Long Term Depression, Metaplasticity and Intrinsic plasticity, together with natural normalization of sensory inputs and Winner-Take-All competitive learning. As a result, KLN performs a Deeper Learning on Datasets showing several high order properties of biological brains as: associative memory, scalability and even continuous learning.…”

Section: Solutions In Biomedicinementioning

confidence: 99%

“…This new model has shown big potential on synthetic inputs and research is now on application performance in complex problems involving real data in comparison with state-of-art supervised and unsupervised techniques. The early detection of cardiovascular disease is an interesting domain addressed in [90] with KLN.…”

Section: Solutions In Biomedicinementioning

confidence: 99%

Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications

et al. 2020

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Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in

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Application of Koniocortex-Like Networks to Cardiac Arrhythmias Classification

Cited by 2 publications

References 23 publications

Competitive Perceptrons: The Relevance of Modeling New Bioinspired Properties Such as Intrinsic Plasticity, Metaplasticity, and Lateral Inhibition of Rate-Coding Artificial Neurons

Competitive Perceptrons: The Relevance of Modeling New Bioinspired Properties Such as Intrinsic Plasticity, Metaplasticity, and Lateral Inhibition of Rate-Coding Artificial Neurons

Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications

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