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Academic Articles & Research Papers
Showing 14 of 14 academic articles
W.D. Penny, David Frost • Medical Decision Making
(1996)
Neural networks are parallel, distributed, adaptive information-processing systems that develop their functionality in response to exposure to information. This paper is a tutorial for researchers intending to use neural nets for medical de...
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DOI: https://doi.org/10.1177/0272989x9601600409
Richard J. Mammone (1994)
Neural Networks for speech processing. Neural Networks in the acquisition of speech by machine. The nervous system - fantasy and reality. Processing of complex stimuli in the mammalian cochlear nucleus. On the possible role of auditory peri...
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C. H. Chen • McGraw-Hill, Inc. eBooks
(1996)
Fuzzy logic principles and algorithms design guidelines for fuzzy logic systems enhanced training algorithms maximum likelihood training temporal difference learning NADINE hybrid learning systems explanation and reasoning within connectivi...
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José M. Benítez, Juan Luis Castro, Ignacio Requena • IEEE Transactions on Neural Networks
(1997)
Artificial neural networks are efficient computing models which have shown their strengths in solving hard problems in artificial intelligence. They have also been shown to be universal approximators. Notwithstanding, one of the major criti...
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DOI: https://doi.org/10.1109/72.623216
Michael Chester • Prentice-Hall, Inc eBooks
(1993)
1. A Structure of an Artificial Neural Network. 2. Applications of Neural Networks. 3. The Early Years. 4. The Hopfield Net. 5. Self Organizing Maps. 6. Backpropagation. 7. Learning Laws and Continued Taxonomy. 8. Adaptive Resonance Theory....
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Laurene V. Fausett • CERN Document Server (European Organization for Nuclear Research)
(1994)
1. Introduction. 2. Simple Neural Nets for Pattern Classification. 3. Pattern Association. 4. Neural Networks Based on Competition. 5. Adaptive Resonance Theory. 6. Backpropagation Neural Net. 7. A Sampler of Other Neural Nets. Glossary. Re...
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Edward Gately (1995)
When applied to the world of finance, neural networks are automated trading systems, based on mapping inputs and outputs for forecasting probable future values. In Neural Networks for Financial Forecasting - the first book to focus on the r...
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Suraj Srinivas, Ravi Kiran Sarvadevabhatla, Konda Reddy Mopuri, Nikita Prabhu et al. • Frontiers in Robotics and AI
(2016)
Traditional architectures for solving computer vision problems and the degree of success they enjoyed have been heavily reliant on hand-crafted features. However, of late, deep learning techniques have offered a compelling alternative -- th...
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cc-by
DOI: https://doi.org/10.3389/frobt.2015.00036
A.K. Jain, Jianchang Mao, K.M. Mohiuddin • Computer
(1996)
Artificial neural nets (ANNs) are massively parallel systems with large numbers of interconnected simple processors. The article discusses the motivations behind the development of ANNs and describes the basic biological neuron and the arti...
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DOI: https://doi.org/10.1109/2.485891
Qi‐Jun Zhang, K.C. Gupta • Artech House, Inc. eBooks
(2000)
From the Publisher:
Discover the new, unconventional alternatives for conquering RF and microwave design and modeling problems using neural networks information processing systems that can learn, generalize, and even allow model developm...
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Fatima Rauf, Muhammad Attique Khan, Ali Kashif Bashir, Kiran Jabeen et al. • Frontiers in Medicine
(2023)
Despite a worldwide decline in maternal mortality over the past two decades, a significant gap persists between low- and high-income countries, with 94% of maternal mortality concentrated in low and middle-income nations. Ultrasound serves ...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fmed.2023.1330218
Jianqing Fan, Cong Ma, Yiqiao Zhong • Statistical Science
(2021)
Deep learning has achieved tremendous success in recent years. In simple words, deep learning uses the composition of many nonlinear functions to model the complex dependency between input features and labels. While neural networks have a l...
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Open Access
DOI: https://doi.org/10.1214/20-sts783
PMC: 8300482
Richard F. Lyon • Cambridge University Press eBooks
(2017)
In order for a digital neocortex to learn a new skill, it will still require many iterations of education, just as a biological neocortex does, but once a single neocortex somewhere and at some time learns something, it can share that knowl...
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Open Access
DOI: https://doi.org/10.1017/9781139051699.031
Paul M. Mather, Stan Openshaw, C. Openshaw • Geographical Journal
(1998)
From the Publisher:
The text provides an introduction to expert systems, neural nets, genetic algorithms, smart systems and artificial life and shows how they are likely to transform geographical enquiry. An integral disk provides examples...
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DOI: https://doi.org/10.2307/3060633