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- W2160586769 abstract "This paper presents analysis and performance-evaluation results for several neural-network-based nondecision-feedback receiver structures, which improve the performance of bandlimited single- and multiamplitude signals transmitted over additive interference channels, such as cochannel interference (CCI) and adjacent channel interference (ACI). In particular, we propose, analyze, and evaluate a training algorithm for Nyquist-filtered single- and multiamplitude signals, based upon a novel nonuniform signal-sampling technique. We also introduce a novel nonlinear activation function for multiamplitude signals and evaluate its performance via computer simulation and in conjunction with various bandlimited signaling formats, detection techniques, and neural-network structures. Bit-error rate (BER) performance-evaluation results of the proposed neural-network receivers for coherent and noncoherent detection of Nyquist- and Butterworth-filtered single- and multiamplitude signals have shown performance improvements in the presence of CCI and ACI." @default.
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- W2160586769 date "1997-01-01" @default.
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- W2160586769 title "Neural-net-based receiver structures for single- and multiamplitude bandlimited signals in CCI and ACI channels" @default.
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- W2160586769 doi "https://doi.org/10.1109/25.618204" @default.
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