Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Frequently Asked Questions
Frequently Asked Questions
Browse
Browse
By Issue Date
By Issue Date
Authors
Authors
Titles
Titles
Subjects
Subjects
Communities & Collections
Communities & Collections
Complexity reduction in radial basis function (RBF) networks by using radial B-spline functions
Date
1998-01-01
Author
Saranlı, Afşar
Baykal, Buyurman
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
2
views
0
downloads
In this paper, new basis consisting of radial cubic and quadratic B-spline functions are introduced together with the CORDIC algorithm, within the context of RBF networks as a means of reducing computational complexity in real-time signal-processing applications. The new basis are compared with two other existing and popularly used basis families, namely the Gaussian functions and the inverse multiquadratic functions (IVMQ) in terms of approximation performance and computational requirements. The new basis are shown to achieve approximation performance very similar to the Gaussian basis functions and are better than the IVMQ functions with less computational load and without any need for approximation methods such as table-lookup.
Subject Keywords
RBF
,
Computational Complexity
,
B-Splines
,
CORDIC
URI
https://hdl.handle.net/11511/42279
Journal
NEUROCOMPUTING
DOI
https://doi.org/10.1016/s0925-2312(97)00078-7
Collections
Department of Electrical and Electronics Engineering, Article