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LiMin Fu (1994)
From the Publisher:
Neural Networks in Computer Intelligence provides basic concepts,algorithms,and analysis of important neural network models developed to date,with emphasis on the importance of knowledge in intelligent system design. Th...
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RT Pramod, Michael A Cohen, Joshua B Tenenbaum, Nancy Kanwisher • eLife
(2022)
Successful engagement with the world requires the ability to predict what will happen next. Here, we investigate how the brain makes a fundamental prediction about the physical world: whether the situation in front of us is stable, and henc...
DOAJ
Open Access (DOAJ)
DOI: 10.7554/eLife.71736
Johann Gasteiger, Jure Zupan • Angewandte Chemie International Edition in English
(1993)
Abstract The capabilities of the human brain have always fascinated scientists and led them to investigate its inner workings. Over the past 50 years a number of models have been developed which have attempted to replicate the brain's vario...
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DOI: https://doi.org/10.1002/anie.199305031
Xin Yao • Proceedings of the IEEE
(1999)
Learning and evolution are two fundamental forms of adaptation. There has been a great interest in combining learning and evolution with artificial neural networks (ANNs) in recent years. This paper: 1) reviews different combinations betwee...
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DOI: https://doi.org/10.1109/5.784219
Kishan G. Mehrotra, Chilukuri Krishna Mohan, Sanjay Ranka • The MIT Press eBooks
(1996)
Elements of Artificial Neural Networks provides a clearly organized general introduction, focusing on a broad range of algorithms, for students and others who want to use neural networks rather than simply study them. The authors, who have ...
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DOI: https://doi.org/10.7551/mitpress/2687.001.0001
Alma Y. Alanis, Gustavo Munoz-Gomez, Nancy F. Ramirez, Oscar D. Sanchez et al. • Algorithms
(2024)
This work introduces an impulsive neural control algorithm designed to mitigate the spread of epidemic diseases. The objective of this paper is the development of a vaccination strategy based on a PIN-type impulsive controller based on an o...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/a17120577
Robert Jane, Tae Young Kim, Emily Glass, Emilee Mossman et al. • Energies
(2021)
To ensure dominance over a multi-domain battlespace, energy and power utilization must be accurately characterized for the dissimilar operational conditions. Using MATLAB/Simulink in combination with multiple neural networks, we created a m...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/en14196049
Maria Grazia Puxeddu, Maria Grazia Puxeddu, Manuela Petti, Manuela Petti et al. • Frontiers in Systems Neuroscience
(2021)
Modular organization is an emergent property of brain networks, responsible for shaping communication processes and underpinning brain functioning. Moreover, brain networks are intrinsically multilayer since their attributes can vary across...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fnsys.2021.624183
Mohamad H. Hassoun • Proceedings of the IEEE
(1996)
From the Publisher:
As book review editor of the IEEE Transactions on Neural Networks, Mohamad Hassoun has had the opportunity to assess the multitude of books on artificial neural networks that have appeared in recent years. Now, in Funda...
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DOI: https://doi.org/10.1109/jproc.1996.503146
Martin Anthony, Peter L. Bartlett • Cambridge University Press eBooks
(1999)
First published in 1999, this book describes theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. R...
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DOI: https://doi.org/10.1017/cbo9780511624216
James A. Anderson • The MIT Press eBooks
(1995)
An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain funct...
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DOI: https://doi.org/10.7551/mitpress/3905.001.0001
Jooho Wang, Sungkyung Park, Chester Sungchung Park • IEEE Access
(2021)
The hardware accelerator controlled by direct memory access (DMA) is greatly influenced by the communication bandwidth from/to DRAM through on-chip buses. This paper proposes a novel performance estimation algorithm to optimize the communic...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2021.3118094
Jiquan Ngiam, Adam Coates, Ahbik Lahiri, Bobby Prochnow et al. • International Conference on Machine Learning
(2011)
The predominant methodology in training deep learning advocates the use of stochastic gradient descent methods (SGDs). Despite its ease of implementation, SGDs are difficult to tune and parallelize. These problems make it challenging to dev...
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Dulani Meedeniya • Chapman & Hall/CRC eBooks
(2023)
This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising....
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public-domain
DOI: https://doi.org/10.1201/9781003390824
Tianjiao Zeng, Yanmin Zhu, Edmund Y. M. Lam • Optics Express
(2021)
Recent years have witnessed the unprecedented progress of deep learning applications in digital holography (DH). Nevertheless, there remain huge potentials in how deep learning can further improve performance and enable new functionalities ...
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Open Access
DOI: https://doi.org/10.1364/oe.443367
Lucas Prado Osco, José Marcato, Ana Paula Marques Ramos, Lúcio André de Castro Jorge et al. • International Journal of Applied Earth Observation and Geoinformation
(2021)
Deep Neural Networks (DNNs) learn representation from data with an impressive capability, and brought important breakthroughs for processing images, time-series, natural language, audio, video, and many others. In the remote sensing field, ...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.jag.2021.102456
Zhiqiang Zhang, Yi Chen Zhao, Xiangke Liao, Wenqiang Shi et al. • Briefings in Functional Genomics
(2018)
Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fo...
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DOI: https://doi.org/10.1093/bfgp/ely030
Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan et al. • BMC Psychiatry
(2025)
Abstract Background Niacin Skin-Flushing Response (NSR) has emerged as a promising objective biomarker for the precise diagnosis of mental disorders. However, its diagnostic potential has been constrained by the limitations of traditional s...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12888-025-07196-2
Ardian Kelmendi, George Pappas • Algorithms
(2025)
The automotive industry increasingly relies on 3D modeling technologies to design and manufacture vehicle components with high precision. One critical challenge is optimizing the placement of latches that secure the dashboard side paneling,...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/a18090553
Yayin Xu, Ying Zhou, Przemysław Sekuła, Lieyun Ding • Developments in the Built Environment
(2021)
The development of artificial intelligence technology is currently bringing about new opportunities in construction. Machine learning is a major area of interest within the field of artificial intelligence, playing a pivotal role in the pro...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.dibe.2021.100045