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A recurrent self-organizing neural fuzzy inference network

Chia-Feng Juang, Chin-Teng Lin
1999 IEEE Transactions on Neural Networks  
A recurrent self-organizing neural fuzzy inference network (RSONFIN) is proposed in this paper.  ...  The structure learning together with the parameter learning forms a fast learning algorithm for building a small, yet powerful, dynamic neural fuzzy network.  ...  In this paper, we shall propose such a recurrent neural fuzzy network.  ... 
doi:10.1109/72.774232 pmid:18252581 fatcat:2dymxeot5bdhzbhzdv2ublzjui

Table of contents

2019 2019 7th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS)  
1 Extracting The Best Features For Predicting The Trend Of Tehran Stock Exchange (TSE) 6 Nonlinear System Identification Using Type-2 Fuzzy Recurrent Wavelet Neural Network 75 Application of Fuzzy Inference  ...  Wavelet Transform 31 Relevant Question Answering in Community Based Networks Using Deep LSTM Neural Networks 36 New Concepts of Matching in Fuzzy Graphs 41 A Fuzzy Directional Median Filter for  ... 
doi:10.1109/cfis.2019.8692170 fatcat:vuckgu24gnezthr5lxel7m2oxe

Prediction of Facebook Post Metrics using Machine Learning [article]

Emmanuel Sam and Sergey Yarushev and Sebastián Basterrech and Alexey Averkin
2018 arXiv   pre-print
In this article, we analyze the efficiency for predicting the post impact of three popular techniques: Support Vector Regression (SVR), Echo State Network (ESN) and Adaptive Network Fuzzy Inject System  ...  In this short paper, we evaluate the performance of three well-known Machine Learning techniques for predicting the impact of a post in Facebook.  ...  Adaptive Network Fuzzy Inject System The Adaptive-Network-Fuzzy Inject System (ANFIS) AN-FIS is the abbreviation Adaptive-Network-Fuzzy Inject System -an adaptive network of fuzzy output.  ... 
arXiv:1805.05579v1 fatcat:iudn3wxsqzcxngrepko5csq5aq

A New Approach for Chaotic Time Series Prediction Using Recurrent Neural Network

Qinghai Li, Rui-Chang Lin
2016 Mathematical Problems in Engineering  
A self-constructing fuzzy neural network (SCFNN) has been successfully used for chaotic time series prediction in the literature.  ...  In this paper, we propose the strategy of adding a recurrent path in each node of the hidden layer of SCFNN, resulting in a self-constructing recurrent fuzzy neural network (SCRFNN).  ...  In particular, recurrent neural network (RNN) has been proved successful in speech processing and adaptive channel equalization.  ... 
doi:10.1155/2016/3542898 fatcat:s6ramypnajc7vb7lg4fxkh7cqy

Guest Editors' Introduction: Neural Networks For Signal Processing

A.G. Constantinides, S. Haykin, Yu Hen Hu, Jenq-neng Hwang, S. Katagiri, Sun-yuan Kung, T.A. Poggio
1997 IEEE Transactions on Signal Processing  
In "Fast Adaptive Digital Equalization by Recurrent Neural Networks," the authors develop a discriminative learning algorithm for recurrent neural networks.  ...  In "Neural-Fuzzy Classification for Segmentation of Remotely Sensed Imageries," remote sensing image segmentation is accomplished using an adaptive resonance theory (ART) classifier, followed by a clustering  ... 
doi:10.1109/tsp.1997.650089 fatcat:se3mm23wzna73iwb6to666b2re

ANFIS for Tamil Phoneme Classification

2019 International Journal of Engineering and Advanced Technology  
neural networks, time delay neural networks, etc. for efficient phoneme recognition.  ...  In this paper, we study the effectiveness of the hybrid architecture, the Adaptive Neuro-Fuzzy Inference System (ANFIS) for capturing the spectral features of the speech signal to handle the problem of  ...  A direct approach that combines a sequence of processes acoustic modeling, language modeling and sequence prediction in continuous speech recognition is developed using Recurrent Neural Networks (RNN)  ... 
doi:10.35940/ijeat.f8804.088619 fatcat:rgefl6a26jcgjmqu2u4cdlcyh4

Page 201 of Neural Computation Vol. 8, Issue 1 [page]

1996 Neural Computation  
A learning algorithm for continually running fully recurrent neural networks. Neural Comp. 1, 270-280. Received April 29, 1994; accepted May 16, 1995.  ...  Acoustics, Speech, Signal Process. 37(3), 328-339. Wan, E. 1993a. Finite impulse response neural networks with applications in time series prediction. Ph.D. dissertation.  ... 

Guest Editorial Special Section on Soft Computing in Industrial Informatics

Xinghuo Yu, Okyay Kaynak, Milos Manic
2012 IEEE Transactions on Industrial Informatics  
He is currently serving as Officer for the IEEE Industrial Electronics Society, chairing technical committee on resilience and security for industrial applications, and is involved in various capacities  ...  He has lead the Computer Science Program at the University of Idaho and is a Director of the Modern Heuristics Group.  ...  The paper "Model Predictive Control of Nonlinear Systems with Unmodeled Dynamics Based on Feedforward and Recurrent Neural Networks," by Wang and Yan, develops a model predictive control for dynamical  ... 
doi:10.1109/tii.2012.2215335 fatcat:6huy7iekabfv7pvgp4ywl6toqe

2020 Index IEEE Transactions on Cognitive and Developmental Systems Vol. 12

2020 IEEE Transactions on Cognitive and Developmental Systems  
A Acevedo-Valle, J.M., Hafner,  ...  in Neural Networks; Yuan, C., Xia, Z., Sun, X., and Wu, Q.M.J., Deep Residual Network With Adaptive Learning Framework for Fingerprint Liveness Detection; TCDS Sept. 2020 461-473 Yuan, H., seeYu, X.,  ...  ., +, TCDS March 2020 73-83 Speech enhancement Ensemble Hierarchical Extreme Learning Machine for Speech Dereverberation.  ... 
doi:10.1109/tcds.2020.3044690 fatcat:yfo6c366aramfdltqegqyqphbq

Emotion Recognition Based on Type-2 Recurrent Wavelet Fuzzy Brain Emotion Learning Network Model

Di Li, Xiangjian Chen, Yifan Zhao
2021 Mathematical Problems in Engineering  
The proposed model takes advantage of type-2 recurrent wavelet fuzzy theory and brain emotional neural network.  ...  The system input data streams are directly imported into the neural network through a type-2 recurrent wavelet fuzzy inference system; then, the results are subsequently piped into sensory and emotional  ...  [14] expanded the conditional probability neural network to a fuzzy form, which is used to predict the emotions expressed by the type-2 recurrent wavelet fuzzy brain emotional learning network can be  ... 
doi:10.1155/2021/9991531 fatcat:szbyyfn7uvfhbjy2auxnodu2lu

NNGD algorithm for neural adaptive filters

D.P. Mandic
2000 Electronics Letters  
However, we believe that, although we have presented just a heuristic approach to such a design, its strength lies in the fact that it opens new research possibilities towards finding more effective design  ...  function and the learning rate within a recurrent neural network', Neural Comput., 1999, 11, (9, pp. 1069-1077 MANDIC, D.P., and CHAMBERS, J.A.: 'Towards an optimal learning rate for backpropagation',  ...  In another experiment, the performance of neural adaptive algorithms was compared with the performances of the LMS and NLMS algorithms for a speech signal s2.  ... 
doi:10.1049/el:20000631 fatcat:cc7plltjmreqdgqio7hhf6dtcy

2014 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 25

2014 IEEE Transactions on Neural Networks and Learning Systems  
Class of Predictive Networks; TNNLS Oct. 2014 1921-1927 Zhang, H., Wang, Z., and Liu, D., A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks; TNNLS Jul. 2014 1229  ...  ., +, TNNLS Apr. 2014 664-676 Fuzzy neural networks A Metacognitive Complex-Valued Interval Type-2 Fuzzy Inference System.  ...  The Field of Values of a Matrix and Neural Networks. Georgiou, G.M., TNNLS Sep. 2014  ... 
doi:10.1109/tnnls.2015.2396731 fatcat:ztnfcozrejhhfdwg7t2f5xlype

Computational Intelligence in Multimedia Processing: Foundation and Trends [chapter]

Aboul-Ella Hassanien, Ajith Abraham, Janusz Kacprzyk, James F. Peters
2008 Studies in Computational Intelligence  
This chapter presents a broad overview of Computational Intelligence (CI) techniques including Neural Network (NN), Particle Swarm Optimization (PSO), Evolutionary Algorithm (GA), Fuzzy Set (FS), and Rough  ...  A review of the current literature on CI based approaches to various problems in multimedia computing such as speech, audio and image processing, video watermarking, content-based multimedia indexing and  ...  Major neural networks that are commonly used for multimedia applications are classified as feed-forward neural network, feedback network or recurrent, self-organizing map and Adaptive Resonance Theory  ... 
doi:10.1007/978-3-540-76827-2_1 fatcat:7jl4ir66vvcl7g436ektwkqwpy

Assessment of Parkinson's disease progression using neural network and ANFIS models

J. Hlavica, M. Prauzek, T. Peterek, P. Musilek
2016 Neural Network World  
Computational methods considered in this paper are artificial neural networks, particularly feedforward networks with several variants of backpropagation learning algorithm, and adaptive network-based  ...  fuzzy inference system (ANFIS).  ...  As for the speech recognition in general, the modern attitudes tend to apply deep bidirectional Long Short-Term Memory recurrent neural networks and deep neural networks [13, 18] .  ... 
doi:10.14311/nnw.2016.26.006 fatcat:ksctcw5j6bdfjpf5rwitpww6fm

The neural paradigm for complex systems: new algorithms and applications

Stefano Squartini, Jinhu Lu, Qinglai Wei
2011 Neural computing & applications (Print)  
Wang et al., the global asymptotic stability problem for a class of recurrent neural networks with multi-time scale is studied.  ...  Wang et al. propose a novel neural network-based iterative adaptive dynamic programming (ADP) algorithm for solving the optimal control problem of a class of nonlinear discrete-time systems with control  ... 
doi:10.1007/s00521-011-0713-4 fatcat:ww5yp7ewd5bs7muhoeos4ip4wu
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