Special Session on "Complex-Valued Neural Networks"
in WCCI / IJCNN 2006 Vancouver

Organized by Akira Hirose
URL: http://www.eis.t.u-tokyo.ac.jp/

Scope and motivation:
The complex-valued neural networks (CVNNs) have been widening the scope of applications not only in electronics and informatics, but also in social systems. The fields are, namely, optoelectronics, imaging, remote sensing, quantum neural devices and systems, intelligent transport systems, and so on. One of the most important characteristics of the CVNNs is the proper treatment of complex-amplitude information, e.g., the treatment of wave-related / rotation-related phenomena such as electromagnetism, lightwaves, quantum waves, oscillatory phenomena even including traffic signal control, and color image processing based on adaptive signal rotation in the RGB space.

Recently there were several CVNN Special Sessions (SSs) in, for example, KES 2001-2003, ICONIP 2002 Singapore, ICANN/ICONIP 2003 Istanbul, and ICONIP 2004 Calcutta, where we had large audience and enjoyed heated and encouraging discussions successfully. The series indicates the increasing importance of this new area.

Now we hold a SS in the WCCI for a wider audience, including fuzzy and evolutionary researchers, to develop further investigations both in theoretical and application fields. We will present the latest results and considerations, and discuss prospective possibilities of the CVNNs. Papers that are, or might be, related to the CVNNs are widely solicited. Topics include, but are not limited to:

* Complex-Valued Neuron Dynamics
* Complex-Valued Associative Memories
* Chaos in Complex Domain
* Spatiotemporal CVNN Processing
* CVNN-based Two-dimensional Information Transform
* CVNN-based Periodic Information Processing
* Fourier Domain CVNN Processing
* Phase-Sensitive Radar Signal Processing
* Coherent Optoelectronic Applications
* Speech, Sonic and Ultrasonic Applications
* Adaptive Quantum Devices
* Quantum Computation and Quantum Neural Networks
* CVNNs in Color Image Processing
* CVNNs in Traffic Control
* CVNNs in Robotics
* Quaternion and Clifford Networks