• Journal of applied mathematics & informatics
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• v.38 no.5_6
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• pp.533-545
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• 2020

We initiate and introduce the notion of binary soft mapping, which is defined on collection of binary soft sets named as binary soft class over two initial universes U₁ and U₂ with fixed set of parameters. We also define and study the properties of binary soft images and binary soft inverse images of binary soft sets. Examples and counter examples are also given in support of presented properties. Moreover, these concepts are applied to the problem of medical diagnosis in medical expert systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.1954-1971
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• 2017

In this work, first, a multiuser detection (MUD) algorithm based on component-level soft interference cancellation and linear minimum mean square error (CLSIC-LMMSE) is proposed, which can enhance the bit error ratio (BER) performance of the traditional SIC-LMMSE-based MUD by mitigating error propagation. Second, for non-binary low density parity check (NB-LDPC) coded high-order modulation systems, when the proposed algorithm is integrated with partial mapping, the receiver with iterative detection and decoding (IDD) achieves not only better BER performance but also significantly computational complexity reduction over the traditional SIC-LMMSE-based IDD scheme. Extrinsic information transfer chart (EXIT) analysis and numerical simulations are both used to support the conclusions.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.1020-1023
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• 2011

In this paper, we present a symbol remapping method of BRGC M-ary QAM signal by using LLR soft bit decision information which is obtained after iterative decoding process. In order to reconstruct estimated transmitted signal constellation, we have to use exponential or hyperbolic tangent(tanh) function resulting in high implementation complexity. The BRGC mapping rule enables us to use a recursive operation. In addtion, we reduce the implementing complexity by using a curve fitting algorithm.