• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1944-1956
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• 2016

The Digital Video Broadcasting-Common Scrambling Algorithm is an ETSI-designated algorithm designed for protecting MPEG-2 signal streams, and it is universally used. Its structure is a typical hybrid symmetric cipher which contains stream part and block part within a symmetric cipher, although the entropy is 64 bits, there haven't any effective cryptanalytic results up to now. This paper studies the security level of CSA against impossible differential cryptanalysis, a 20-round impossible differential for the block cipher part is proposed and a flaw in the cipher structure is revealed. When we attack the block cipher part alone, to recover 16 bits of the initial key, the data complexity of the attack is O(2^44.5), computational complexity is O(2^22.7) and memory complexity is O(2^10.5) when we attack CSA-BC reduced to 21 rounds. According to the structure flaw, an attack on CSA with block cipher part reduced to 21 rounds is proposed, the computational complexity is O(2^21.7), data complexity is O(2^43.5) and memory complexity is O(2^10.5), we can recover 8 bits of the key accordingly. Taking both the block cipher part and stream cipher part of CSA into consideration, it is currently the best result on CSA which is accessible as far as we know.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.22-28
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• 2015

In this paper, we propose a new computationally efficient joint iterative multi-input multi-output (MIMO) detection scheme using a soft interference cancellation and minimum mean squared-error (SIC-MMSE) method. The critical computational burden of the SIC-MMSE scheme lies in the multiple inverse operations of the complex matrices. We find a new way which requires only a single matrix inversion by utilizing the Taylor series expansion of the matrix, and thus the computational complexity can be reduced. The computational complexity reduction increases as the number of antennas is increased. The simulation results show that our method produces almost the same performances as the conventional SIC-MMSE with reduced computational complexity.

• ETRI Journal
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• v.38 no.2
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• pp.326-336
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• 2016

We propose and describe new error control algorithms for redundant residue number systems (RRNSs) and residue number system product codes. These algorithms employ search techniques for obtaining error values from within a set of values (that contains all possible error values). For a given RRNS, the error control algorithms have a computational complexity of $t{\cdot}O(log_2\;n+log_2\;{\bar{m}})$ comparison operations, where t denotes the error correcting capability, n denotes the number of moduli, and ${\bar{m}}$ denotes the geometric average of moduli. These algorithms avoid most modular operations. We describe a refinement to the proposed algorithms that further avoids the modular operation required in their respective first steps, with an increase of ${\lceil}log_2\;n{\rceil}$ to their computational complexity. The new algorithms provide significant computational advantages over existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2141-2155
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• 2020

In order to meet the requirements of background change, illumination variation, moving shadow interference and high accuracy in object detection of moving camera, and strive for real-time and high efficiency, this paper presents an object detection algorithm based on sparse approximation recursion and sparse coding migration in subspace. First, low-rank sparse decomposition is used to reduce the dimension of the data. Combining with dictionary sparse representation, the computational model is established by the recursive formula of sparse approximation with the video sequences taken as subspace sets. And the moving object is calculated by the background difference method, which effectively reduces the computational complexity and running time. According to the idea of sparse coding migration, the above operations are carried out in the down-sampling space to further reduce the requirements of computational complexity and memory storage, and this will be adapt to multi-scale target objects and overcome the impact of large anomaly areas. Finally, experiments are carried out on VDAO datasets containing 59 sets of videos. The experimental results show that the algorithm can detect moving object effectively in the moving camera with uniform speed, not only in terms of low computational complexity but also in terms of low storage requirements, so that our proposed algorithm is suitable for detection systems with high real-time requirements.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.1
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• pp.89-96
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• 2013

This paper presents an improved clutter signal removal algorithm using Singular Value Decomposition(SVD). For indoor positioning system using IR-UWB Radar, the target signal is extracted from received signal. We use clutter signal removal algorithm using SVD for target signal extraction. Clutter signal removal algorithm using SVD has the advantage of operation but the disadvantage of high computational complexity. In this paper, we propose a method to improve computational complexity. As the experimental results, it is confirmed that the method presented in this paper improve the computational complexity of clutter removal algorithm using SVD.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1187-1190
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• 1998

In this paper we propose a new efficient generalized sidelobe canceller(GSC) algorithm, using the efficient frequency domain LMS algorithm, which has much less weights to update. We only update part of all the weights according to magnitude of each frequency bin. So, the new proposed GSC algorithm, which is called censored GSC(C-GSC), can greatly reduce the computational complexity.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.45-48
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• 2005

In this paper, we propose a new fast running FIR filter structure that improves the convergence speed of adaptive signal processing and reduces the computational complexity. The proposed filter is applied to wavelet based adaptive algorithm. Actually we compared the performance of the proposed algorithm with other algorithm using computer simulation of adaptive noise canceler based on synthesis speech. As the result, We know the proposed algorithm is prefer than the existent algorithm.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2E
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• pp.38-46
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• 1997

The objective of the paper is to compare the computational complexity of five algorithms for computing time-domain second-order Volterra filter outputs in terms of number of real multiplication and addition operations required for implementation. This study shows that if the filter memory length is greater that or equal to 16, the fast algorithm using the overlap-save method and the frequency-domain symmetry properties of the quadratic coefficients is the most efficient among the algorithms investigated in this paper, When the filter memory length is less than 16, the algorithm using the time-domain symmetry properties is better than any other algorithm.

• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.342-347
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• 2018

We proposed a fast detection of copy-move image forgery using four step search algorithm in the spatial domain. In the four-step search algorithm, the search area is 21 (-10 ~ +10), and the number of pixels to be scanned is 33. Our algorithm reduced computational complexity more than conventional copy move image forgery methods. The proposed method reduced 92.34 % of computational complexity compare to exhaustive search algorithm.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.5
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• pp.1-9
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• 1996

In this paper, we propose an efficient computational algorithm that can reduce significantly the computational complexity of the ML optimum multiuser detector known as the most excellent detector in synchronous code division multiple access channels. The proposed detector uses the sequential detection algorithm based on the alternating maximization appraoch to obtain the ML estimates. As initial estimates for this sequential algorithm, we can use the estimated values obtained by the conventional single-user detector, the linear decorrelating multiuser detector, or the decorrelating decision-feedback muliuser detector, the linear decorrelating multiuser detector, or the decorrelating decision-feedback multiuser detector. We have performed computer simulations in order to see the convergence behaviors and the detection performance of the propsoed algorithm in terms of initial algorithms and the number of users, and then to compare the computational complexity with that of the ML optimum multiuser detector. From the results, we have seen that the proposed alternating maximization detector has nearly equal detction performance with that of the ML optimum multiuser detctor in only a few iteration.