Journal ArticleDOI
Efficient architecture for Bayesian equalization using fuzzy filters
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TLDR
It is shown that the fuzzy equalizer in general demands much lower computational complexity than the optimum equalizer and ways to further reduce the computation complexity of fuzzy equalizers are proposed and their performance evaluated.Abstract:
A normalized Bayesian solution is derived for digital communication channel equalization which uses estimates of scalar channel states. This equalizer is termed as a normalized Bayesian equalizer with scalar channel states (NBEST). The relationship between the NBEST and fuzzy equalizers is derived and computational aspects of fuzzy equalizers are investigated using different types of fuzzy basis functions. It is shown that the fuzzy equalizer in general demands much lower computational complexity than the optimum equalizer. Ways to further reduce the computation complexity of fuzzy equalizers is proposed and their performance evaluated. A novel scheme to select a subset of channel states close to the received vector, resulting in considerable reduction in the computational complexity, is also proposed. A fuzzy equalizer with this modified membership function is shown to perform close to the Bayesian equalizer.read more
Citations
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Interval type-2 fuzzy logic systems: theory and design
Qilian Liang,Jerry M. Mendel +1 more
TL;DR: An efficient and simplified method to compute the input and antecedent operations for interval type-2 FLSs: one that is based on a general inference formula for them is proposed.
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Type-2 fuzzy logic systems
TL;DR: A type-2 fuzzy logic system (FLS) is introduced, which can handle rule uncertainties and its implementation involves the operations of fuzzification, inference, and output processing, which consists of type reduction and defuzzification.
Journal ArticleDOI
Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters
Qilian Liang,Jerry M. Mendel +1 more
TL;DR: This filter is applied to equalization of a nonlinear time-varying channel and it is demonstrated that it can implement the Bayesian equalizer for such a channel, has a simple structure, and provides fast inference.
Journal ArticleDOI
Uncertainty, fuzzy logic, and signal processing
TL;DR: It is demonstrated, by means of examples, that atype-2 FLS can outperform a type-1 FLS for one-step prediction of a Mackey}Glass chaotic time series whose measurements are corrupted by additive noise, and equalization of a nonlinear time-varying channel.
Journal ArticleDOI
A type-2 neuro-fuzzy system based on clustering and gradient techniques applied to system identification and channel equalization
TL;DR: This paper presents the development of novel type-2 neuro-fuzzy system for identification of time-varying systems and equalization ofTime-Varying channels using clustering and gradient algorithms, which combines the advantages oftype-2 fuzzy systems and neural networks.
References
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TL;DR: This paper gives a tutorial exposition of the Viterbi algorithm and of how it is implemented and analyzed, and increasing use of the algorithm in a widening variety of areas is foreseen.
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Fast learning in networks of locally-tuned processing units
John Moody,Christian J. Darken +1 more
TL;DR: This work proposes a network architecture which uses a single internal layer of locally-tuned processing units to learn both classification tasks and real-valued function approximations (Moody and Darken 1988).