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An Intelligent Call Admission Control Decision Mechanism for Wireless Networks [article]

Ramesh Babu H.S., Gowrishankar, Satyanarayana P.S
2010 arXiv   pre-print
of the neural networks .The model is based on Recurrent Radial Basis Function Networks (RRBFN) which have better learning and adaptability that can be used to develop the intelligent system to handle  ...  This paper proposes a fuzzy neural approach for call admission control in a multi class traffic based Next Generation Wireless Networks (NGWN).  ...  network is the Radial Basis Function Network(RBFN).  ... 
arXiv:1004.4444v1 fatcat:67lkeq2zqfbx7mz3ysuonhsbz4

A QoS Provisioning Recurrent Neural Network based Call Admission Control for beyond 3G Networks [article]

Ramesh Babu H.S., Gowrishankar, Satyanarayana P.S
2010 arXiv   pre-print
The model is based on recurrent radial basis function networks which have better learning and adaptability that can be used to develop intelligent system to handle the incoming traffic in an heterogeneous  ...  This paper proposes a fuzzy neural approach for making the call admission control decision in multi class traffic based Next Generation Wireless Networks (NGWN).  ...  The Radial Basis Function Network (RBFN) has a faster convergence property than a multilayer Perceptron (MLP) because the RBFN has a simple structure.  ... 
arXiv:1004.3563v1 fatcat:7dtpo3anfbgl3hokcqrvtxj4p4

The Use of Graph Databases for Artificial Neural Networks

Doğa Barış ÖZDEMİR, Ahmet Cumhur KINACI
2021 Journal of Advanced Research in Natural and Applied Sciences  
An artificial neural network can be structurally expressed as a graph. Therefore, it would be much more useful to store ANN models in a database and use the graph database as this database system.  ...  The developed software platform is aimed to increase the representation power of the currently used methods by transferring the models developed in the popular ANN frameworks used today.  ...  Ahmet Cumhur KINACI: Designed and analyzed the artificial neural network processes on graphs approach. Conflicts of Interest The authors declare no conflict of interest.  ... 
doi:10.28979/jarnas.890552 fatcat:qbpxorsr3zb3zb6vhbccdsgcvu

A comparative and comprehensive study of prediction of Parkinson's disease

N. Prasath, Vigneshwaran Pandi, Sindhuja Manickavasagam, Prabu Ramadoss
2021 Indonesian Journal of Electrical Engineering and Computer Science  
A range of those techniques, including SVM, Artificial Neural Network, Naive Bayes, Kernel based extreme learning through subtractive clustering landscapes, Random Forest, The Multi-Layer Perceptron with  ...  Result: It has been observed that many researches have been done in identifying the PD yet there is a need of suitable method or algorithm to improve the prediction of PD which will help in the clinical  ...  The proposed arrangement of obsessive voice from typical voice by Sellam and Jagadeesan [49] uses support vector machine (SVM) and radial basis functional neural network (RBFNN) in the implementation  ... 
doi:10.11591/ijeecs.v23.i3.pp1748-1760 fatcat:a2mlp3vn6ffcvjwubvilia47fe

Acoustic Feature Extraction and Optimized Neural Network based Classification for Speaker Recognition

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
We accomplish this evaluation through a comparative analysis of various recognition of speaker approaches and compare the results of the same  ...  In this paper, literatures are surveyed on recognition of speaker through the neural network using an optimization algorithm that has developed from the previous years for ASR systems.  ...  The radial basis function is one common kind of activation function which is based on supervised DNN models. Layers MLP consists of three or more layers.  ... 
doi:10.35940/ijitee.i7760.078919 fatcat:r2ku2ubwyrejto22ayagljepvy

An Optimized Recursive General Regression Neural Network Oracle for the Prediction and Diagnosis of Diabetes

Dana Bani-Hani, Pruthak Patel, Tasneem Alshaikh
2018 Global Journal of Computer Science and Technology  
Diabetes is a serious, chronic disease that has been seeing a rise in the number of cases and prevalence over the past few decades.  ...  Several classifiers, along with the R-GRNN Oracle and the GRNN Oracle, are applied to the dataset, they are: Support Vector Machine (SVM), Multilayer Perceptron (MLP), Probabilistic Neural Network (PNN  ...  Kayaer and Yildirim (2003) applied an MLP, Radial Basis Function (RBF), and a General Regression Neural Network (GRNN) on the Pima Indian Diabetes dataset.  ... 
doi:10.34257/gjcstdvol19is2pg1 fatcat:dgvewnce4vaxhi7jv6p3njd6t4

WDSAE-DNDT BASED SPEECH FLUENCY DISORDER CLASSIFICATION

Sheena Christabel Pravin, M. Palanivelan
2022 Malaysian Journal of Computer Science  
In this paper, Weight Decorrelated Stacked Autoencoder-Deep Neural Decision Trees (WDSAE-DNDT), a novel hybrid model is proposed for automating the assessment of children's speech fluency disorders by  ...  Further analysis was carried out to check the impact of tree cut points for each feature and epochs on the accuracy of prediction of the hybrid model.  ...  The Author is the Co-Investigator of the project and the Co-author is the Principal Investigator.  ... 
doi:10.22452/mjcs.vol35no3.3 fatcat:llrndelrrbde7do7qxmhrvacma

Active authentication for mobile devices utilising behaviour profiling

Fudong Li, Nathan Clarke, Maria Papadaki, Paul Dowland
2013 International Journal of Information Security  
In comparison to point-of-entry based approaches, behaviour profiling provides a significant improvement in both the security afforded to the device and user convenience.  ...  In order to balance the trade-off between security and usability, the framework is designed in a modular way that will not reject user access based upon a single application activity but a number of consecutive  ...  These were the Radial Basis Function (RBF) neural network, the Feed-Forward Multi-Layered Perceptron (FF MLP) neural network and a Rule-based approach.  ... 
doi:10.1007/s10207-013-0209-6 fatcat:4i4gaoov3vgujpxli4ltm2jula

Human Face Detection Techniques: A Comprehensive Review and Future Research Directions

Md Khaled Hasan, Md. Shamim Ahsan, Abdullah-Al-Mamun, S. H. Shah Newaz, Gyu Myoung Lee
2021 Electronics  
In our study, however, we cover detailed technical explanations of face detection algorithms and various recent sub-branches of the neural network.  ...  We present detailed comparisons among the algorithms in all-inclusive and under sub-branches.  ...  Radial Basis Function Neural Network (RBFNN) The radial basis function neural network (RBFNN) was presented by Broomhead and Lowe in 1988 [166, 205] . RBFNN has similarities structurally with BPNN.  ... 
doi:10.3390/electronics10192354 fatcat:oy7adwj6cjefnm66cn5kxrybni

Comprehensive Review of Artificial Neural Network Applications to Pattern Recognition

Oludare Isaac Abiodun, Aman Jantan, Abiodun Esther Omolara, Kemi Victoria Dada, Abubakar Malah Umar, Okafor Uchenwa Linus, Humaira Arshad, Abdullahi Aminu Kazaure, Usman Gana, Mahammad Ubale Kiru
2019 IEEE Access  
The era of artificial neural network (ANN) began with a simplified application in many fields and remarkable success in pattern recognition (PR) even in manufacturing industries.  ...  Hence, there is a need for state-of-the-art in neural networks application to PR to urgently address the abovehighlights problems for more successes.  ...  The architecture of a radial basis function network (RBFN). FIGURE 15 . 15 FIGURE 15. A single-layer NN. FIGURE 16 . 16 FIGURE 16. The architecture of multilayer feedforward neural network.  ... 
doi:10.1109/access.2019.2945545 fatcat:cyove346d5bdri5gvczpmycc6i

Neighbouring Proximity - An Key Impact Factor of Deep Machine Learning

Hongyuan Shi, Yunke Li, Liang Chen, Fan Jiang
2018 2018 IEEE 17th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)  
It has an outstanding capability to extract and represent the features of raw data and it has been applied to many domains, such as image processing, pattern recognition, computer vision, machine translation  ...  While the advantages of deep learning methods are widely accepted, the limitations are not well studied.  ...  Convolutional Neural Network A modern convolutional neural network is a multi-layer artificial neural network.  ... 
doi:10.1109/icci-cc.2018.8482089 dblp:conf/IEEEicci/ShiLCJ18 fatcat:t7misysu3bdhjgbx2uwnbrshf4

Use Brain-Like Audio Features to Improve Speech Recognition Performance

Junyi Wang, Bingyao Li, Jiahong Zhang, Yaxiang Fan
2022 Journal of Sensors  
heavily on neural network algorithms, and has extremely high technical requirements.  ...  effects depend on large batches of training, which requires a large amount of computational resources for the problem.  ...  Finally, radial basis neural network (RBFNN for short) is one of the most typical radial basis theories combined with the depth of the three levels of the second which is a forward neural network algorithm  ... 
doi:10.1155/2022/6742474 fatcat:wtfvm6bcwfcrtjeh2nm3n4i3vq

Ensemble methods for spoken emotion recognition in call-centres

Donn Morrison, Ruili Wang, Liyanage C. De Silva
2007 Speech Communication  
This comparison demonstrates the advantages and disadvantages of both acquisition methods and how these methods affect the end application of vocal emotion recognition.  ...  This research aims to improve the automatic perception of vocal emotion in two ways.  ...  The authors are grateful for the use of the speech database provided by Mabix International as well as the speech database provided by Tin Lay Nwe.  ... 
doi:10.1016/j.specom.2006.11.004 fatcat:pe5nsnvxrbc4heqdgpwdypb6xm

A Review of Location Encoding for GeoAI: Methods and Applications [article]

Gengchen Mai, Krzysztof Janowicz, Yingjie Hu, Song Gao, Bo Yan, Rui Zhu, Ling Cai, Ni Lao
2021 arXiv   pre-print
neural networks.  ...  A common need for artificial intelligence models in the broader geoscience is to represent and encode various types of spatial data, such as points (e.g., points of interest), polylines (e.g., trajectories  ...  He was the Chief scientist and co-founder of Mosaix.ai, a voice search AI startup. He is an expert in Machine Learning (ML), Knowledge Graph (KG) and Natural Language Understanding (NLU).  ... 
arXiv:2111.04006v1 fatcat:ymv527cygbaavbrhi2xe5xtcni

A Survey on Signal Processing Based Pathological Voice Detection Techniques

Rumana Islam, Mohammed Tarique, Esam Abdel-Raheem
2020 IEEE Access  
In the first part, we present background information including causes of voice disability, current procedures and practices, voice features, and classifiers.  ...  Voice disability is a barrier to effective communication. Around 1.2% of the World's population is facing some form of voice disability.  ...  RBF Radial basis function RBFNN Radial Basis Functional Neural Networks SVD Saarbruecken Voice Database SVM Support vector machine SPI Soft phonation index SIR Spectral Flatness of the Residue  ... 
doi:10.1109/access.2020.2985280 fatcat:htzmng6lazaqxheiwf2omrtzfi
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