Connectionists: [CFP] Special Issue in IEEE TNNLS, "Complex- and Hypercomplex-Valued Neural Networks"

[Akira Hirose]

*Call for Papers: Deadline **_January 15, 2013_**

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
SPECIAL ISSUE ON COMPLEX- AND HYPERCOMPLEX-VALUED NEURAL NETWORKS
<http://www.eis.t.u-tokyo.ac.jp/news/NNTC_CVNN/>*

http://www.eis.t.u-tokyo.ac.jp/news/NNTC_CVNN/

Complex-valued neural networks (CVNNs) exhibit very desirable
characteristics in their learning, self-organizing, and processing
dynamics. They are perfectly suited to deal with complex amplitude,
composed of amplitude and phase, which is one of the core concepts in
physical systems dealing with electromagnetic, light, sonic/ultrasonic,
and quantum waves (electron and superconducting waves). This, together
with the widespread use of analytic signals, gives them a critical
advantage in practical applications in diverse fields of engineering,
where signals are routinely analyzed and processed in time/space,
frequency, and phase domains. CVNNs are closely related also to brain
dynamics, e.g., in the analysis of theta rhythm in Hippocampus where the
phase shift plays an important role in place cell firing. In addition,
broad-sense CVNNs such as quaternion and Clifford neural networks, as
well as kernel and reservoir approaches, underpin unique new directions
in color-information treatment, robotics and control. To further promote
research activities in this area, IEEE Transactions on Neural Networks
plans to publish a Special Issue on "Complex- and hypercomplex-valued
neural networks" to be published in January 2014.

*Scope of the Special Issue*
We welcome theoretical papers, application papers, as well as survey
papers. Topics include, but are not limited to:
* Theoretical aspects of CVNNs such as complex-valued activation
functions, gradient, and stability
* Learning/Self-organization algorithms and processing dynamics in CVNNs
* Chaos in the complex domain, coherence, and causality
* Complex-valued associative memories and attractor networks
* Feedforward/Recurrent CVNNs for time series analysis and classification
* Phase-only and phase-sensitive signal processing and nonlinear
filtering using CVNNs
* Distributed, widely linear, sparse, and kernel CVNN approaches
* Pattern recognition, classification and time series prediction using CVNNs
* Applications of CVNNs in image processing, speech processing and
bioinformatics
* Frequency- , time-frequency, and spatio-temporal domain CVNN processing
* Quantum computation and quantum neural networks
* CVNNs for trajectory tracking, robotics and control
* Clifford, quaternion, and multidimensional neural networks

*IMPORTANT DATES *
15 January 2013 -- Deadline for manuscript submission
15 August 2013 -- Notification to authors
15 September 2013 -- Deadline for submission of revised manuscripts
1 October 2013 -- Final decision
January 2014 -- Special issue publication in the IEEE TNNLS

*GUEST EDITORS *
Akira Hirose, The University of Tokyo, Japan, ahirose at ee.t.u-tokyo.ac.jp
Igor Aizenberg, Texas A&M University - Texarcana, U.S.A.,
Igor.Aizenberg at tamut.edu
Danilo P. Mandic, Imperial College, U.K., d.mandic at imperial.ac.uk

*SUBMISSION INSTRUCTIONS*
1. Read the information for Authors at http://cis.ieee.org/publications.html
2. Submit the manuscript by *_January 15, 2013_* at the IEEE-TNNLS
webpage http://mc.manuscriptcentral.com/tnnls and follow the submission
procedure. Please, clearly indicate on the first page of the manuscript
and the Author's Cover Letter that the manuscript has been submitted to
the Special Issue on /Complex- and Hypercomplex-Valued Neual Networks/.
Send also an email to the guest editors to notify of your submission.
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