• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.7
• /
• pp.3353-3370
• /
• 2016

The way of combination of Product Perfect Codes (PPCs) is based on the theory of short codes constructing long codes. PPCs have larger embedding rate than Hamming codes by expending embedding columns in a coding block, and they have been proven to enhance the performance of the F₅ steganographic method. In this paper, the proposed modified product codes called MPCs are introduced as an efficient way to embed more data than PPCs by increasing 2^r₂-1-r₂ embedding columns. Unlike PPC, the generation of the check matrix H in MPC is random, and it is different from PPC. In addition a simple solving way of the linear algebraic equations is applied to figure out the problem of expending embedding columns or compensating cases. Furthermore, the MPCs over ℤ₄ have been proposed to further enhance not only the performance but also the computation speed which reaches O(n₁+σ). Finally, the proposed ℤ₄-MPC intends to maximize the embedding rate with maintaining less distortion , and the performance surpasses the existing improved product perfect codes. The performance of large embedding rate should have the significance in the high-capacity of covert communication.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.9
• /
• pp.3458-3481
• /
• 2021

Existing methods for blind identification of linear block codes without a candidate set are mainly built on the Gauss elimination process. However, the fault tolerance will fall short when the intercepted bit error rate (BER) is too high. To address this issue, we apply the reverse algebra approach and propose a novel "two-step-screening" algorithm by solving the linear error equations on the binary Galois field, or GF(2). In the first step, a recursive matrix partition is implemented to solve the system linear error equations where the coefficient matrix is constructed by the full codewords which come from the intercepted noisy bitstream. This process is repeated to derive all those possible parity-checks. In the second step, a check matrix constructed by the intercepted codewords is applied to find the correct parity-checks out of all possible parity-checks solutions. This novel "two-step-screening" algorithm can be used in different codes like Hamming codes, BCH codes, LDPC codes, and quasi-cyclic LDPC codes. The simulation results have shown that it can highly improve the fault tolerance ability compared to the existing Gauss elimination process-based algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.5 no.1
• /
• pp.41-51
• /
• 2001

In this paper, we presented that the performance of the TCM(Trellis Coded Modulation) using the Euclidean distance is better than that of the convolutional code using the hamming distance under the same bandwidth efficiency. And the TCM DECODER for next generation mobile communication replacing the using convolutional decoder is implemented. Also, for the implementation of the TCM DECODER, the convolutional decoder and the TCM decoder were made by C-language and simulated under AWGN channel with respect to the hard decision and the soft decision. So we proved that performance of the TCM is better than that of the convolutional code. From this result, TCM DECODER, of which constraint length is 3, 5 or 7 and which use the soft decision method, was implemented using the AHDL(Altera Hardware Description Language) and fortified using the Max+plus H version 8.2 of Altera corporation.

• Journal of Communications and Networks
• /
• v.17 no.4
• /
• pp.351-361
• /
• 2015

In this paper, a new decoding scheme is proposed to improve the error correcting performance of low-density parity-check (LDPC) codes in high signal-to-noise ratio (SNR) region by using post-processing. It behaves as follows: First, a conventional LDPC decoding is applied to received LDPC codewords one by one. Then, we count the number of word errors in a predetermined number of decoded codewords. If there is no word error, nothing needs to be done and we can move to the next group of codewords with no delay. Otherwise, we perform a proper post-processing which produces a new soft-valued codeword (this will be fully explained in the main body of this paper) and then apply the conventional LDPC decoding to it again to recover the unsuccessfully decoded codewords. For the proposed decoding scheme, we adopt a simple product code structure which contains LDPC codes and simple algebraic codes as its horizontal and vertical codes, respectively. The decoding capability of the proposed decoding scheme is defined and analyzed using the parity-check matrices of vertical codes and, especially, the combined-decodability is derived for the case of single parity-check (SPC) codes and Hamming codes used as vertical codes. It is also shown that the proposed decoding scheme achieves much better error correcting capability in high SNR region with little additional decoding complexity, compared with the conventional LDPC decoding scheme.

• Journal of the Institute of Convergence Signal Processing
• /
• v.3 no.4
• /
• pp.67-73
• /
• 2002

There have been increased concerns on mobile stratospheric communication system(SCS) for the purpose of advanced service of personal and high speed communication systems. In fact, this SCS is considered and studied for IMT-2000 service by ITU. Although, it is important to make accurate channel model for prediction of the SCS performance, there is no measured channel data in this system. Thus, in this paper, we estimate the performance of SCS bye use of channel model provided by Corazza(2) and modified by You(3). And also, the effects of channel codings on system performance are analyzed by deriving bit error performance based on realistic Rician log-normal fading channel models. The performance results are divided into three kinds of areas with three kinds of elevation angles 20$^\cire$, 45$^\cire$, and 80$^\cire$. And also the effects of forward error correction channel codings on system performance with Hamming(7,4), HCH( IS,7) and convolutional code of constraint length 3 and code rate R=1/2.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.4
• /
• pp.819-826
• /
• 2018

The generalized Hamming weight is one of the important parameters of the linear code. It determines the performance of the code when the linear codes are applied to a cryptographic system. In addition, when the block code is decoded by soft decision using the lattice diagram, it becomes a measure for evaluating the state complexity required for the implementation. In particular, a bit-parallel multiplier on finite fields based on trinomials have been studied. Cellular automata(CA) has superior randomness over LFSR due to its ability to update its state simultaneously by local interaction. In this paper, we deal with the efficient synthesis of the pseudo random number generator, which is one of the important factors in the design of effective cryptosystem. We analyze the property of the characteristic polynomial of the simple 90/150 transition rule block, and propose a synthesis algorithm of the reversible 90/150 CA corresponding to the trinomials $x^2^n+x^{2^n-1}+1$($n{\geq}2$) and the 90/150 reversible CA(RCA) corresponding to the maximum weight polynomial with $2^n$ degree by using this rule block.

• The Journal of the Korea Contents Association
• /
• v.5 no.4
• /
• pp.188-196
• /
• 2005

This paper presents a new test data compression and low power scan test method that can reduce test time and power consumption. A proposed method can reduce the scan-in power and test data volume using a modified scan cell reordering algorithm and hybrid adaptive encoding method. Hybrid test data compression method uses adaptively the Golomb codes and run-length codes according to length of runs in test data, which can reduce efficiently the test data volume compare to previous method. We apply a scan cell reordering technique to minimize the column hamming distance in scan vectors, which can reduce the scan-in power consumption and test data. Experimental results for ISCAS 89 benchmark circuits show that reduced test data and low power scan testing can be achieved in all cases. The proposed method showed an about a 17%-26% better compression ratio, 8%-22% better average power consumption and 13%-60% better peak power consumption than that of previous method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.7
• /
• pp.2599-2613
• /
• 2015

Multi-index hashing (MIH) is the state-of-the-art method for indexing binary codes, as it di-vides long codes into substrings and builds multiple hash tables. However, MIH is based on the dataset codes uniform distribution assumption, and will lose efficiency in dealing with non-uniformly distributed codes. Besides, there are lots of results sharing the same Hamming distance to a query, which makes the distance measure ambiguous. In this paper, we propose a data-oriented multi-index hashing method (DOMIH). We first compute the covariance ma-trix of bits and learn adaptive projection vector for each binary substring. Instead of using substrings as direct indices into hash tables, we project them with corresponding projection vectors to generate new indices. With adaptive projection, the indices in each hash table are near uniformly distributed. Then with covariance matrix, we propose a ranking method for the binary codes. By assigning different bit-level weights to different bits, the returned bina-ry codes are ranked at a finer-grained binary code level. Experiments conducted on reference large scale datasets show that compared to MIH the time performance of DOMIH can be improved by 36.9%-87.4%, and the search accuracy can be improved by 22.2%. To pinpoint the potential of DOMIH, we further use near-duplicate image retrieval as examples to show the applications and the good performance of our method.

• Smart Structures and Systems
• /
• v.16 no.2
• /
• pp.243-262
• /
• 2015

Optimal sensor placement (OSP) is a critical issue in construction and implementation of a sophisticated structural health monitoring (SHM) system. The uncertainties in the identified structural parameters based on the measured data may dramatically reduce the reliability of the condition evaluation results. In this paper, the information entropy, which provides an uncertainty metric for the identified structural parameters, is adopted as the performance measure for a sensor configuration, and the OSP problem is formulated as the multi-objective optimization problem of extracting the Pareto optimal sensor configurations that simultaneously minimize the appropriately defined information entropy indices. The nondirective movement glowworm swarm optimization (NMGSO) algorithm (based on the basic glowworm swarm optimization (GSO) algorithm) is proposed for identifying the effective Pareto optimal sensor configurations. The one-dimensional binary coding system is introduced to code the glowworms instead of the real vector coding method. The Hamming distance is employed to describe the divergence of different glowworms. The luciferin level of the glowworm is defined as a function of the rank value (RV) and the crowding distance (CD), which are deduced by non-dominated sorting. In addition, nondirective movement is developed to relocate the glowworms. A numerical simulation of a long-span suspension bridge is performed to demonstrate the effectiveness of the NMGSO algorithm. The results indicate that the NMGSO algorithm is capable of capturing the Pareto optimal sensor configurations with high accuracy and efficiency.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.10a
• /
• pp.553-559
• /
• 2004

In todays security industry, personal identification is also based on biometric. Biometric identification is performed basing on the measurement and comparison of physiological and behavioral characteristics, Biometric for recognition includes voice dynamics, signature dynamics, hand geometry, fingerprint, iris, etc. Iris can serve as a kind of living passport or living password. Iris recognition system is the one of the most reliable biometrics recognition system. This is applied to client/server system such as the electronic commerce and electronic banking from stand-alone system or networks, ATMs, etc. A new algorithm using nonlinear function in recognition process is proposed in this paper. An algorithm is proposed to determine the localized iris from the iris image received from iris input camera in client. For the first step, the algorithm determines the center of pupil. For the second step, the algorithm determines the outer boundary of the iris and the pupillary boundary. The localized iris area is transform into polar coordinates. After performing three times Wavelet transformation, normalization was done using sigmoid function. The converting binary process performs normalized value of pixel from 0 to 255 to be binary value, and then the converting binary process is compare pairs of two adjacent pixels. The binary code of the iris is transmitted to the by server. the network. In the server, the comparing process compares the binary value of presented iris to the reference value in the University database. Process of recognition or rejection is dependent on the value of Hamming Distance. After matching the binary value of presented iris with the database stored in the server, the result is transmitted to the client.