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المؤلفTran D.T.
المؤلفKiranyaz, Mustafa Serkan
المؤلفGabbouj M.
المؤلفIosifidis A.
تاريخ الإتاحة2022-04-26T12:31:20Z
تاريخ النشر2020
اسم المنشورIEEE Transactions on Neural Networks and Learning Systems
المصدرScopus
المعرّفhttp://dx.doi.org/10.1109/TNNLS.2019.2914082
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85081242263&doi=10.1109%2fTNNLS.2019.2914082&partnerID=40&md5=b238251898daf81e7a3d6c57c579dbb5
معرّف المصادر الموحدhttp://hdl.handle.net/10576/30609
الملخصThe traditional multilayer perceptron (MLP) using a McCulloch-Pitts neuron model is inherently limited to a set of neuronal activities, i.e., linear weighted sum followed by nonlinear thresholding step. Previously, generalized operational perceptron (GOP) was proposed to extend the conventional perceptron model by defining a diverse set of neuronal activities to imitate a generalized model of biological neurons. Together with GOP, a progressive operational perceptron (POP) algorithm was proposed to optimize a predefined template of multiple homogeneous layers in a layerwise manner. In this paper, we propose an efficient algorithm to learn a compact, fully heterogeneous multilayer network that allows each individual neuron, regardless of the layer, to have distinct characteristics. Based on the complexity of the problem, the proposed algorithm operates in a progressive manner on a neuronal level, searching for a compact topology, not only in terms of depth but also width, i.e., the number of neurons in each layer. The proposed algorithm is shown to outperform other related learning methods in extensive experiments on several classification problems.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعLearning systems
Multilayers
Architecture learning
Feed-forward network
generalized operational perceptron (GOP)
Mcculloch-pitts neuron models
Multi layer perceptron
Multi-layer network
Nonlinear thresholding
Progressive learning
Neurons
algorithm
classification
factual database
Algorithms
Databases, Factual
Neural Networks, Computer
العنوانHeterogeneous Multilayer Generalized Operational Perceptron
النوعArticle
الصفحات710-724
رقم العدد3
رقم المجلد31
dc.accessType Abstract Only


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