• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.10-14
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• 2006

Many clustering methods have been studied. For the most part of these methods may be needed to determine the number of clusters. But, there are few methods for determining the number of population clusters objectively. It is difficult to determine the cluster size. In general, the number of clusters is decided by subjectively prior knowledge. Because the results of clustering depend on the number of clusters, it must be determined seriously. In this paper, we propose an efficient method for determining the number of clusters using hybrid' self organizing map and new criterion for evaluating the clustering result. In the experiment, we verify our model to compare other clustering methods using the data sets from UCI machine learning repository.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.78-89
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• 2013

This paper proposes a high-throughput and multi-mode quasi-cyclic (QC) low-density parity-check (LDPC) decoder based on a fully parallel structure. The proposed QC-LDPC decoder employs the fully parallel structure to provide very high throughput. The high interconnection complexity, which is the general problem in the fully parallel structure, is solved by using a broadcasting-based sum-product algorithm and proposing a low-complexity cyclic shift network. The high complexity problem, which is caused by using a large amount of check node processors and variable node processors, is solved by proposing a combined check and variable node processor (CCVP). The proposed QC-LDPC decoder can support the multi-mode decoding by proposing a routing-based interconnection network, the flexible CCVP and the flexible cyclic shift network. The proposed QC-LDPC decoder is operated at 100 MHz clock frequency. The proposed QC-LDPC decoder supports multi-mode decoding and provides 8.1 Gbps throughput for a (1944, 1620) QC-LDPC code.