Supervised Learning with Complex-valued Neural Networks

• Main Authors: Suresh, Sundaram. (Author), Sundararajan, Narasimhan. (Author), Savitha, Ramasamy. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
• Series: Studies in Computational Intelligence, 421
• Subjects: Engineering.; Computational Intelligence.; Signal, Image and Speech Processing.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-29491-4

Recent advancements in the field of telecommunications, medical imaging and signal processing deal with signals that are inherently time varying, nonlinear and complex-valued. The time varying, nonlinear characteristics of these signals can be effectively analyzed using artificial neural networks.�...

Table of Contents:

• Introduction
• Fully Complex-valued Multi Layer Perceptron Networks
• Fully Complex-valued Radial Basis Function Networks
• Performance Study on Complex-valued Function Approximation Problems
• Circular Complex-valued Extreme Learning Machine Classifier
• Performance Study on Real-valued Classification Problems
• Complex-valued Self-regulatory Resource Allocation Network
• Conclusions and Scope for FutureWorks (CSRAN).