2011 Fiscal Year Final Research Report
Construction of Machine Learning Algorithm Based on Fixed Point Theory and Its Application to Wireless Communication Systems
| Project/Area Number |
20760252
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Communication/Network engineering
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| Research Institution | Niigata University (2010-2011)
The Institute of Physical and Chemical Research (2008-2009) |
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Principal Investigator |
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| Project Period (FY) |
2008 – 2011
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| Keywords | 信号処理 |
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| Research Abstract |
Based on fixed point theory, we have obtained the following outcomes.(1) We have derived a reduced-rank adaptive algorithm, analyzed its convergence properties, and shown that it ameliorates the convergence rate considerably with low computational complexity.(2) We have introduced the new concept of time-varying metric producing a general framework to analyze the convergence properties of a number of adaptive algorithms in a unified fashion.(3) We have imported the concept of feasibility splitting to adaptive signal processing, derived an efficient adaptive algorithm to exploit a variety of information that is expressed in multiple domains, analyzed its convergence properties, and shown its efficacy in SIMO/MIMO wireless communication systems.
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