Multi-Valued and Universal Binary Neurons

System identification and modelling based on a double modified multi-valued neural network

Grasso, F., Luchetta, A., Manetti, S., et al. (2013) · Analog Integrated Circuits and Signal Processing · doi:10.1007/s10470-013-0211-y · Cited by 4

A new multi-valued neural network for the extraction of lumped models of analog circuits

Grasso, F., Luchetta, A., Manetti, S., et al. (2011) · Analog Integrated Circuits and Signal Processing · doi:10.1007/s10470-011-9733-3 · Cited by 4

Design of Experiments Technique Applied to Artificial Neural Network Models for FPSO Mooring System Analysis

Nikkhah, E., Fernandes, A. C., & Caprace, J. (2023) · Journal of Marine Science and Engineering · doi:10.3390/jmse11112194 · Cited by 4

Pattern stability on complex-valued associative memory by local iterative learning scheme

Yamamoto, H., Isokawa, T., Nishimura, H., et al. (2012) · doi:10.1109/scis-isis.2012.6505125 · Cited by 3

Complex valued neural network modelling of the balun of a biconical antenna

Bonci, A., Carobbi, C. F. M., & Luchetta, A. (2014) · doi:10.1109/isemc.2014.6899024 · Cited by 3

LUPU-Net: a new improvement proposal for encoder-decoder architecture

Arpacı, S. A., & VARLI, S. (2021) · International Advanced Researches and Engineering Journal · doi:10.35860/iarej.939243 · Cited by 3

An Improved Lightweight Network Using Attentive Feature Aggregation for Object Detection in Autonomous Driving

Kalgaonkar, P., & El‐Sharkawy, M. (2023) · Journal of Low Power Electronics and Applications · doi:10.3390/jlpea13030049 · Cited by 3

TTK: A toolkit for Tunisian linguistic analysis

Mekki, A., Zribi, I., Ellouze, M., et al. (2024) · Computer Speech & Language · doi:10.1016/j.csl.2023.101617 · Cited by 3

Multi-valued and Universal Binary Neurons: New Applications in Intelligent Image Processing

Aizenberg, I. N. (2001) · Lecture notes in computer science · doi:10.1007/3-540-45493-4_46 · Cited by 3

Complex-Valued Neurons with Phase-Dependent Activation Functions

Aizenberg, I. N. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13232-2_1 · Cited by 3

A modified error-correction learning rule for multilayer neural network with multi-valued neurons

Aizenberg, I. N. (2013) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2013.6706842 · Cited by 3

The Genetic Code as a Multiple-Valued Function and Its Implementation Using Multilayer Neural Network Based on Multi-Valued Neurons

Aizenberg, I. N., & Moraga, C. (2007) · Proceedings/Proceedings - International Symposium on Multiple-Valued Logic · doi:10.1109/ismvl.2007.54 · Cited by 3

Mapping Decision Diagrams for Multiple-Valued Logic Functions into Threshold Logic Networks

Stanković, M., Stojković, S., & Moraga, C. (2011) · Proceedings/Proceedings - International Symposium on Multiple-Valued Logic · doi:10.1109/ismvl.2011.28 · Cited by 3

Deep Learning: New Engine for the Study of Material Microstructures and Physical Properties

卢, 果. (2019) · Modern Physics · doi:10.12677/mp.2019.96026 · Cited by 3

Auto-regressive multiple-valued logic neurons with sequential Chua’s oscillator back-propagation learning for online prediction and synchronization of chaotic trajectories

Mozaffari, A., Azad, N. L., & Fathi, A. (2015) · International Journal of Intelligent Computing and Cybernetics · doi:10.1108/ijicc-11-2014-0046 · Cited by 2

Finite convergence of the learning algorithms for a modified multi-valued neuron

Xu, D., & Liang, S. (2014) · doi:10.1109/ijcnn.2014.6889696 · Cited by 2

Multi-valued neuron with new learning schemes

Wu, S.-F., & Lee, S.-J. (2013) · 2022 International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2013.6707132 · Cited by 2

MVN_CNN and FCNN for endocardial edge detection

Ketout, H., Gu, J. J., & Horne, G. (2011) · Middle East Conference on Biomedical Engineering · doi:10.1109/mecbme.2011.5752102 · Cited by 2

Learning in networks: Complex-valued neurons, pruning, and rule extraction

Żurada, J. M., Aizenberg, I. N., & Mazurowski, M. A. (2008) · International IEEE Conference on Intelligent Systems (IS) · doi:10.1109/is.2008.4670394 · Cited by 2

Fully Coupled and Feedforward Neural Networks with Complex-Valued Neurons

Żurada, J. M., & Aizenberg, I. N. (2008) · Studies in computational intelligence · doi:10.1007/978-3-540-74930-1_5 · Cited by 2

Learning of the Non-threshold Functions of Multiple-Valued Logic by a Single Multi-valued Neuron with a Periodic Activation Function

Aizenberg, I. N. (2010) · Proceedings/Proceedings - International Symposium on Multiple-Valued Logic · doi:10.1109/ismvl.2010.15 · Cited by 2

How to impede the external manipulation of autonomous cars?

Kiss, G. J. (2022) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-219277 · Cited by 2

The Role of Artificial Intelligence in Radiation Therapy Treatment Planning: A Comprehensive Review

John, M., & Mina, J. (2025) · Journal of Cancer Treatment and Research · doi:10.11648/j.jctr.20251303.14 · Cited by 1

Reconstructing Algorithmic Trading in the Age of Generative AI: Implications for Market Structure, Regulation, and Epistemology

Arias-Barrera, L. C. (2025) · Revista e-mercatoria · doi:10.18601/16923960.v25n1.08 · Cited by 2

Optimizing ship voyages: a review on gas emissions, fuel consumption, and prediction

Bahrami, N. (2026) · Journal of Ocean Engineering and Marine Energy · doi:10.1007/s40722-026-00469-2 · Cited by 4

A new stability condition for discrete time recurrent neural networks with complex-valued linear threshold neurons

Zhou, W., & Żurada, J. M. (2014) · doi:10.1109/ijcnn.2014.6889621 · Cited by 1

Multi-Valued Neuron with a periodic activation function - as part of a multi-layered Neural Network

Lupea, V. M. (2013) · IEEE International Symposium on Applied Machine Intelligence and Informatics (SAMI) · doi:10.1109/sami.2013.6480958 · Cited by 1

Learning Transformations with Complex-Valued Neurocomputing

Nitta, T. (2012) · International Journal of Organizational and Collective Intelligence · doi:10.4018/joci.2012040103 · Cited by 2

A double neural network for interpretation of the frequency response in the electrical equipments

Grasso, F., Luchetta, A., Manetti, S., et al. (2012) · IEEE International Conference on Intelligent Systems · doi:10.1109/is.2012.6335140 · Cited by 1

Identification of improper processes by variable tap-length complex-valued adaptive filters

Ujang, B. C., Took, C. C., & Mandic, D. P. (2010) · 2022 International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2010.5596607 · Cited by 1

A class of discrete-time recurrent neural networks with multivalued neurons

Zhou, W., & Żurada, J. M. (2009) · doi:10.1109/ijcnn.2009.5178721 · Cited by 1

Intelligent Edge Detection using a CUDA Simulator of Multilayer Neural Network Based on Multi-Valued Neurons

Wilson, J. G., & Aizenberg, I. N. (2012) · Cited by 1

Method and Application of Visual Relationship Detection Based on Deep Learning

汤, 婧. (2022) · Journal of Image and Signal Processing · doi:10.12677/jisp.2022.113016 · Cited by 1

Equivalence Classes of Boolean Functions

Stanković, R. S., Stanković, S., Astola, H., et al. (2010) · Synthesis lectures on digital circuits and systems · doi:10.1007/978-3-031-79812-2_1 · Cited by 1

Understanding the Flows of Signals and Gradients: A Tutorial on Algorithms Needed to Implement a Deep Neural Network from Scratch

Klęsk, P. (2024) · Applied Sciences · doi:10.3390/app14219972 · Cited by 2

Sentiment Analysis from Tweets using Convolutional Neural Networks

Pek, M., & Turan, M. (2021) · THE JOURNAL OF CIEES · doi:10.48149/jciees.2021.1.1.2 · Cited by 1

Subgroup Preference Neural Network

Elgharabawy, A., Prasad, M., & Lin, C. (2021) · Sensors · doi:10.3390/s21186104 · Cited by 1

Christine the Murderer Artificial Intelligence

Kiss, G. J. (2022) · International Conference on Control, Decision and Information Technologies (CoDIT) · doi:10.1109/codit55151.2022.9803913 · Cited by 2

Towards Natural Language Understanding using Multimodal Deep Learning

Bös, S. (2017) · Research Repository (Delft University of Technology) · Cited by 1

Deep Learning

Schmidhuber, J. (2017) · Springer eBooks · doi:10.1007/978-1-4899-7687-1_909 · Cited by 1

Neural networks regularization through representation learning

Belharbi, S. (2018) · theses.fr (ABES) · doi:10.70675/0e1f98e2zabc7z497bzaf40z433d33a78b60 · Cited by 3

Multi-Valued Neurons: Hebbian and Error-Correction Learning

Aizenberg, I. N. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-21501-8_5

Spectral representations of discrete functions

Fu, C. (2005) · doi:10.32657/10356/46880

Classification of the Images of Gene Expression Patterns Using Neural Networks Based on Multi-valued Neurons

Aizenberg, I. N., Myasnikova, E. M., & Samsonova, M. G. (2001) · Lecture notes in computer science · doi:10.1007/3-540-45723-2_26

On the Projection of k-Valued Non-linearly Separable Problems into m-Valued Linearly Separable Problems

Aizenberg, I. N. (2011) · Studies in computational intelligence · doi:10.1007/978-3-642-20206-3_15

Lumped model identification based on a double multi-valued neural network and frequency response analysis

Luchetta, A., & Manetti, S. (2012) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas.2012.6271811

Multi-valued neuron with a periodic activation function — Influence of l-periodic parameter over the learning process

Lupea, V. M. (2013) · IEEE International Symposium on Computational Intelligence and Informatics (CINTI) · doi:10.1109/cinti.2013.6705189

A hybrid Multi-valued neuron based network for the identification of lumped models

Grasso, F., Luchetta, A., Manetti, S., et al. (2010) · doi:10.1109/sm2acd.2010.5672354

CNN-based language and interpreter for image processing on GPUs

Dolan, R., & DeSouza, G. N. (2011) · International Journal of Parallel Emergent and Distributed Systems · doi:10.1080/17445760.2010.505194

Analog system modeling based on a double modified complex valued neural network

Luchetta, A., Manetti, S., & Piccirilli, M. C. (2013) · 2022 International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2013.6707136

Testing complex-valued perceptron properties experimentally

Ахметшин, Р. М., Giniyatullin, V. M., Кирлан, С. А., et al. (2013) · Optical Memory and Neural Networks · doi:10.3103/s1060992x13010013

Identification of systems for modelling and diagnosis based on a double multi-valued neural network

Grasso, F., Luchetta, A., Manetti, S., et al. (2012) · International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design · doi:10.1109/smacd.2012.6339393

Novel Complex Vauled Neural Networks.

Ahuja, N., & Murthy, G. R. (2006) · CDES

Multi-Valued Neuron with a periodic activation function - learning with negative examples

M, L. V., & Cernăzanu-Glăvan, C. (2014) · doi:10.1109/saci.2014.6840067

The most robust design for digital logics of multiple variables based on neurons with complex-valued weights

Lü, W., Lin, M., & Sun, L. (2009) · Journal of Zhejiang University. Science A · doi:10.1631/jzus.a0820238

Soft Computing Methods for Prediction of Replication Origins in Caudoviruses

Cruz‐Cano, R., & Aizenberg, I. N. (2008) · Proceedings/Proceedings - International Symposium on Multiple-Valued Logic · doi:10.1109/ismvl.2008.29

Effect of Positive Weight Diagonal Elements on MVN Neural Networks in Associative Memory Design

Zhou, W., Xie, Y., Tang, D., et al. (2015) · International Symposium on Computational Intelligence and Design · doi:10.1109/iscid.2015.121

Complex-valued support vector machines based on multi-valued neurons

Shinoda, H., & Hattori, M. (2018) · International Conference on Information and Communications Technology (ICOIACT) · doi:10.1109/icoiact.2018.8350666

Neurocomputing: An Introduction

Tripathi, B. K. (2014) · Studies in computational intelligence · doi:10.1007/978-81-322-2074-9_1

Optimization in ICN

Dutta, N., Sarma, H. K. D., Jadeja, R. B., et al. (2021) · Practical networking · doi:10.1007/978-3-030-46736-4_7

Machine Learning and Other Techniques in Artificial Intelligence

Xia, M. (2023) · Springer eBooks · doi:10.1007/978-981-99-5925-9_2

Challenges and Opportunities in Integrating Machine Learning with Medical Imaging: A Comprehensive Review

Chaudhary, M., & Agrawal, H. (2023) · International Conference on Informatics (ICI) · doi:10.1109/ici60088.2023.10421032

Algebra and Error-Correcting Codes

Alpay, D. (2024) · Chapman mathematical notes · doi:10.1007/978-3-031-51822-5_4

Complements in Linear Algebra

Alpay, D. (2024) · Chapman mathematical notes · doi:10.1007/978-3-031-51822-5_2

Introduction

Wang, W. (2024) · Springer eBooks · doi:10.1007/978-981-97-5333-8_1

Information Systems and Automated Census Using Object Detection for the Management and Valuation of Built Cultural Heritage

Doria, E., & Morandotti, M. (2024) · Lecture notes in civil engineering · doi:10.1007/978-3-031-71855-7_19

Decision support systems in the diagnosis of urological diseases

Vasilyev, A. O., Говоров, А. В., Arutyunyan, P. A., Kim, Y. A., Sarukhanian, A., & DIu, P. (2024) · Cancer Urology · doi:10.17650/1726-9776-2024-20-3-159-167 · Cited by 3

A Novel Complex Encoder Transformation MLMVN Framework for Marine Vessels Detection Using SAR Images

Dashondhi, G. K., Sharma, S., Dasaundhi, G., Arun, P. V., Bhardwaj, A., & Buddhiraju, K. M. (2025) · Journal of the Indian Society of Remote Sensing · doi:10.1007/s12524-025-02122-1

Estimation of fluid saturation and pressure distribution throughout a reservoir using machine learning techniques

Rahman, A., Daoud, G., Shirif, E., et al. (2025) · Petroleum Research · doi:10.1016/j.ptlrs.2025.08.007

Synthèse de correcteurs s’adaptant à des critères multiples de haut niveau par la commande prédictive et les réseaux de neurones

Pouilly-Cathelain, M. (2020) · theses.fr (ABES) · doi:10.70675/ee63a4dbzd95cz4971zb16czd660ee807250

Investigating new Machine Learning approaches for financial fraud detection and survival analysis in insurance industries

Yankol‐Schalck, M. (2022) · theses.fr (ABES) · doi:10.70675/539531e4za6a6z4a53za634z00fcd670513f

Distributed computing at the smart device edge

Feltin, T. (2023) · doi:10.70675/2f7e1eb6zdb29z4aa3zb2d2za399e1df734b

A Review of Machine Learning Applications in Monitoring Data Processing for Underground Engineering

Li, M., Zhang, Y., Wang, Y., & Wang, Y. (2026) · Buildings · doi:10.3390/buildings16163285

Novel Complex-Valued Neural Networks with Magnitude and Phase Quantization

Murthy, G. R., Mayukha, M., Veeramachaneni, S. D., & Valle, M. E. (2026) · International Conference on Emerging Techniques in Computational Intelligence (ICETCI) · doi:10.1109/icetci71772.2026.11710683

Susquehanna Chorale Spring Concert "Roots and Wings"

Hawkins, D. (2017)

Prim�rzerlegung in Steinschen Algebren

Förster, O. (1964) · Mathematische Annalen · doi:10.1007/bf01362567 · Cited by 32

�ber unirationale Scharen auf algebraischen Mannigfaltigkeiten

Reich, L. (1966) · Mathematische Annalen · doi:10.1007/bf01364537 · Cited by 4

Algebraic Set Operations, Multifunctions, and Indefinite Integrals

Jovanović, M. V., & Jungić, V. M. (1996) · Mathematics Magazine · doi:10.2307/2691279

On Almost α(Λ, sp)-continuous Multifunctions

Boonpok, C., & Khampakdee, J. (2022) · European Journal of Pure and Applied Mathematics · doi:10.29020/nybg.ejpam.v15i2.4277 · Cited by 5