A Novel Kernel for RBF Based Neural Networks
Joint Authors
Aftab, Wasim
Moinuddin, Muhammad
Shaikh, Muhammad Shafique
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-19
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Radial basis function (RBF) is well known to provide excellent performance in function approximation and pattern classification.
The conventional RBF uses basis functions which rely on distance measures such as Gaussian kernel of Euclidean distance (ED) between feature vector and neuron’s center, and so forth.
In this work, we introduce a novel RBF artificial neural network (ANN) where the basis function utilizes a linear combination of ED based Gaussian kernel and a cosine kernel where the cosine kernel computes the angle between feature and center vectors.
Novelty of the proposed work relies on the fact that we have shown that there may be scenarios where the two feature vectors (FV) are more prominently distinguishable via the proposed cosine measure as compared to the conventional ED measure.
We discuss adaptive symbol detection for multiple phase shift keying (MPSK) signals as a practical example to show where the angle information can be pivotal which in turn justifies our proposed RBF kernel.
To corroborate our theoretical developments, we investigate the performance of the proposed RBF for the problems pertaining to three different domains.
Our results show that the proposed RBF outperforms the conventional RBF by a remarkable margin.
American Psychological Association (APA)
Aftab, Wasim& Moinuddin, Muhammad& Shaikh, Muhammad Shafique. 2014. A Novel Kernel for RBF Based Neural Networks. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1033579
Modern Language Association (MLA)
Aftab, Wasim…[et al.]. A Novel Kernel for RBF Based Neural Networks. Abstract and Applied Analysis No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1033579
American Medical Association (AMA)
Aftab, Wasim& Moinuddin, Muhammad& Shaikh, Muhammad Shafique. A Novel Kernel for RBF Based Neural Networks. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1033579
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1033579