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Development Of Novel Neuro-Fuzzy Techniques For Adaptive Systems

机译:自适应系统的新型神经模糊技术的发展

摘要

Novel approaches for designing adaptive schemes based on neuro-fuzzy platform have been developed. Two kinds of adaptive schemes namely, adaptive equalization and system identification are implemented using the developed proposed techniques. The Radial basis function (RBF) equalizer is chosen as a case study for adaptive equalization of the digital communication channels. An efficient method for reducing the centers of a RBF equalizer based on eigenvalue analysis is presented. The efficiency of the method is further verified for RBF equalizers with decision feedback for tackling channels with overlapping channel states. A comparative study between the proposed center reduction technique and other center reduction techniques for the RBF equalizer is discussed. In another breakthrough a parallel interpretation of the ANFIS (adaptive network based fuzzy inference systems) architecture is proposed. This approach helps to investigate the role of the fuzzy inference part and the s...
机译:开发了基于神经模糊平台的自适应方案设计新方法。使用所提出的技术实现了两种自适应方案,即自适应均衡和系统识别。选择径向基函数(RBF)均衡器作为数字通信信道自适应均衡的案例研究。提出了一种基于特征值分析的降低RBF均衡器中心的有效方法。对于具有判定反馈的RBF均衡器,该方法的效率进一步得到了验证,以解决具有重叠信道状态的信道。讨论了所提出的RBF均衡器的中心缩减技术与其他中心缩减技术之间的比较研究。在另一个突破中,提出了对ANFIS(基于自适应网络的模糊推理系统)体系结构的并行解释。这种方法有助于调查模糊推理部分和解决方案的作用。

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    Vamsi Krishna T;

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  • 年度 2006
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