• Journal of Communications and Networks
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• v.14 no.3
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• pp.280-285
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• 2012

We propose self-encoded spread spectrum with two different iterative detection methods in multi-channel communication. The centralized iterative detection outperforms the iterative detection distributed over multiple channels. The results show that self-encoded spread spectrum with the centralized iterative detection is an excellent candidate for cognitive radio network.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.258-265
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• 2013

In this study, we investigate the multi-carrier spread spectrum (MCSS) communication system which adopts the self-encoded spread spectrum in a downlink synchronous channel. It is very difficult to completely eliminate the frequency offset in practical channel scenarios. We demonstrate that the self-encoded MCSS (SE-MCSS) with iterative despreading manifests a remarkable immunity to residual frequency offset. The SE-MCSS can be an excellent candidate for the future generation of wireless services.

• Journal of Communications and Networks
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• v.9 no.1
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• pp.50-55
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• 2007

We propose to apply chip interleaving and iterative detection to self-encoded multiple access (SEMA) communications. In SEMA, the spreading code is obtained from user bit information itself without using a pseudo noise code generator. The proposed scheme exploits the inherent diversity in self encoded spread spectrum signals. Chip interleaving not only increases the diversity gain, but also enhances the performance of iterative detection. We employ user-mask and interference cancellation to decouple self-encoded multiuser signals. This paper describes the proposed scheme and analyzes its performance. The analytical and simulation results show that the proposed system can achieve a 3 dB power gain and possess a diversity gain that can yield a significant performance improvement in both Rayleigh and multipath fading channels.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.276-282
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• 2013

Self-encoded spread spectrum (SESS) is a novel modulation technique that acquires its spreading code from a random information source, rather than using the traditional pseudo-random noise (PN) codes. In this paper, we present our study of the SESS system performance under pulsed-noise jamming and show that iterative detection can significantly improve the bit error rate (BER) performance. The jamming performance of the SESS with correlation detection is verified to be similar to that of the conventional direct sequence spread spectrum (DSSS) system. On the other hand, the time diversity detection of the SESS can completely mitigate the effect of jamming by exploiting the inherent temporal diversity of the SESS system. Furthermore, iterative detection with multiple iterations can not only eliminate the jamming completely but also achieve a gain of approximately 1 dB at $10^{-3}$ BER as compared with the binary phase shift keying (BPSK) system under additive white gaussian noise (AWGN) by effectively combining the correlation and time diversity detections.

• Journal of Communications and Networks
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• v.6 no.1
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• pp.9-18
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• 2004

Self-encoded multiple access (SEMA) is a unique realization of random spread spectrum. As the term implies, the spreading code is obtained from the random digital information source instead of the traditional pseudo noise (PN) code generators. The time-varying random codes can provide additional security in wireless communications. Multi-rate transmissions or multi-level grade of services are also easily implementable in SEMA. In this paper, we analyze the performance of SEMA in additive white Gaussian noise (AWGN) channels and Rayleigh fading channels. Differential encoding eliminates the BER effect of error propagations due to receiver detection errors. The performance of SEMA approaches the random spread spectrum discussed in literature at high signal to noise ratios. For performance improvement, we employ multiuser detection and Turbo coding. We consider a downlink synchronous system such as base station to mobile communication though the analysis can be extended to uplink communications.

• BMB Reports
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• v.30 no.1
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• pp.18-20
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• 1997

Lycopersicon peruvianum shows a gametophytic self-incompatibility (GSI). GSI is controlled by a single locus (S locus) with multiple alleles. S ribonucleases encoded in S alleles cosegregate with their phenotypes of GSI in genetic cross. To understand the genetic role of S allele in L peruvianum, two large genomic fragments isolated previously were analyzed with total genomic DNAs from several tomato lines generated by cross-pollination. Southern blot analysis with the S allele fragments as probes revealed that the flanking region of S allele contained the highly homologous regions. It is speculated that they may play an important role to prevent genetic cross by self-pollination.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.497-504
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• 2020

Constructing speaker embeddings in speaker verification is an important issue. In general, a self-attention mechanism has been applied for speaker embedding encoding. Previous studies focused on training the self-attention in a high-level layer, such as the last pooling layer. In this case, the effect of low-level layers is not well represented in the speaker embedding encoding. In this study, we propose Masked Cross Self-Attentive Encoding (MCSAE) using ResNet. It focuses on training the features of both high-level and low-level layers. Based on multi-layer aggregation, the output features of each residual layer are used for the MCSAE. In the MCSAE, the interdependence of each input features is trained by cross self-attention module. A random masking regularization module is also applied to prevent overfitting problem. The MCSAE enhances the weight of frames representing the speaker information. Then, the output features are concatenated and encoded in the speaker embedding. Therefore, a more informative speaker embedding is encoded by using the MCSAE. The experimental results showed an equal error rate of 2.63 % using the VoxCeleb1 evaluation dataset. It improved performance compared with the previous self-attentive encoding and state-of-the-art methods.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.851-854
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• 1998

Recently efficient image coding algorithms using zerotree have been proposed. In these methods, the locations of nonzero wavelet coefficients are encoded with a tree structure, called zerotree, which can exploit the self-similarity of the wavelet pyramid decomposition across different scales. These are very effective, especially in low bit rate image coding. In this paper, two zerotree image coding algorithms, EZW and SPIHT, are briefly introduced, and a new zerotree searching scheme is proposed to emphasize the significance of a wavelet coefficient by its orientations as well as its scale.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.161-164
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• 2000

Recently efficient image coding using zerotree have been proposed. In these methods, the locations of nonzero wavelet coefficient are encoded with a tree structure, called zerotree, which can exploit the self-similarity of the wavelet pyramid decomposition across different scales. These are very especially in low bit rate image coding. In this paper, two zerotree image coding algorithm, EZW and SPHIT are briefly introduced, and a new zerotree searching scheme is proposed to emphasize the significance of a wavelet coefficient by its orientation as well as its scale.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.532-534
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• 1990

We suggest a new energy function that improves the area complexity of the Hopfield Crossbar Network. Through converting data representation to an encoded format, we reduce the number of nodes of the network, and thus reduce the entire size. We apply this approach to the layer assignment problem, and use the modified delayed self-feedback Hopfield Network. Area complexity of the existing network for layer assignment ploblem is improved from O( $N^2L^2$ ) to O($N^2$(log L)$^2$).