In many important application areas such as signal processing, pattern recognition, control and communication, nonlinear adaptive systems are needed to approximate underlying mappings through learning from examples. In order for approximations to be suffciently accurate, a good performance is required for nonlinear adaptive systems. Meanwhile, many applications, especially those in emerging areas of wireless communication and networking , require the learning to be done in real-time in order to adapt to a rapidly
By: Sheng Ma, Chuanyi Ji
Published in: RC22600 in 2002
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