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Predictive Control of Radio Telescope Using Multi-layer Perceptron Neural Network
2013Radio telescope (RT) installations are highly valuable assets and during the period of their service life they need regular repair and maintenance to be carried out for delivering satisfactory performance and minimizing downtime. With the growing automation technologies, predictive control can prove to be a better approach than the traditionally ...
Sergej Jakovlev +3 more
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On-chip multi-layer perceptron and time-delay neural networks for phoneme recognition
2005 12th IEEE International Conference on Electronics, Circuits and Systems, 2005This paper presents a back-propagation neural network for phoneme recognition. The neural network has been implemented on-chip using 0.35 mum three-metal dual-poly CMOS technology. The results obtained for multi-layer perceptrons (MLP) and time-delay neural network (TDNN) implementations for phoneme recognition systems are presented.
Edward Gatt +2 more
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An Immune and a Gradient-Based Method to Train Multi-Layer Perceptron Neural Networks
The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006Multi-layer perceptron (MLP) neural network training can be seen as a special case of function approximation, where no explicit model of the data is assumed. In its simplest form, it corresponds to finding an appropriate set of weights that minimize the network training and generalization errors.
Rodrigo Pasti, Leandro Nunes de Castro
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Prediction of Heart Disease Using Multi-Layer Perceptron Neural Network and Support Vector Machine
International Conference on Electrical Information and Communication Technologies, 2019In recent years, heart disease is one of the major causes of death. So it is necessary to design a system that correctly diagnoses heart disease. In this study, we have proposed two classifiers.
Md. Nahiduzzaman +3 more
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[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1992
Nonlinear equalizers find use in communication applications where the channel distortion is too severe for a linear equalizer to handle. Because of their nonlinear capability and other attractive properties, neural networks have become appealing candidates for equalization problems.
Marcia Peng +2 more
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Nonlinear equalizers find use in communication applications where the channel distortion is too severe for a linear equalizer to handle. Because of their nonlinear capability and other attractive properties, neural networks have become appealing candidates for equalization problems.
Marcia Peng +2 more
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Modelling the infiltration process with a multi-layer perceptron artificial neural network [PDF]
Hydrological Sciences Journal, 2006 Abstract Infiltration is a significant process which controls the fate of water in a catchment. Over the years, many infiltration models have been developed which are either physically based, conceptual or empirical. The literature shows that a model's applicability will always be limited to its context (such as location, availability of data, etc ...
exaly +2 more sources
A hybrid recommender system using multi layer perceptron neural network
2018 8th Conference of AI & Robotics and 10th RoboCup Iranopen International Symposium (IRANOPEN), 2018Recommender systems try to personalized preferences, obviously this predicting based on previous users taste. Many RS suffer from Cold-start problem, it pertains to the issue which the system cannot invoke any reasoning for users whom they have not yet accumulated proper information.
Didar Divani Sanandaj, Sasan H. Alizadeh
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Classification of Sensorimotor Rhythms Based on Multi-layer Perceptron Neural Networks
2020 International Conference on Development and Application Systems (DAS), 2020Sensorimotor rhythms are represented by mu rhythm with 8-12Hz frequency band and beta rhythm with the 12-30Hz frequency range. The movement or preparation of the movement is typically accompanied by a decrease of the mu and beta rhythms, especially in the contralateral area of the movement, which is a piece of very important knowledge for the ...
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