• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.49-59
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• 2009

In this paper a watermarking algorithm is proposed to optimize the capacity of the digital watermark insertion in an experimental threshold using the characteristics of human visual system(HVS), adaptive scale factors, and weight functions based on discrete wavelet transform. After the original image is decomposed by a 3-level discrete wavelet transform, the watermarks for capacity optimization are inserted into all subbands except the baseband, by applying the important coefficients from the experimental threshold in the wavelet region. The adaptive scale factors and weight functions based on HVS are considered for the capacity optimization of the digital watermark insertion in order to enhance the robustness and invisibility. The watermarks are consisted of gaussian random sequences and detected by correlation. The experimental results showed that this algorithm can preserve a fine image quality against various attacks such as the JPEG lossy compression, noise addition, cropping, blurring, sharpening, linear and non-linear filtering, etc.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.52-58
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• 2013

This paper proposes an adaptive algorithm based on a method of dynamic error signal generation suitable for signal state by examining the equalizer output signal in blind equalization. In the proposed method, it estimates the error signals using single modulus and multiple modulus each effective to the early stage of equalization or steady-state, and it generates a new error signal from the two error estimates. Two equalizer structures are implemented and their performances are compared: 1-equalizer structure that generates a new error signal by combining the two error estimates weightedly and updates the equalizer using this, and 2-equalizer structure that updates two equalizers respectively depending on the weights of the two error signals. In the proposed method, as the error signals were generated optimally before and after the initial convergence respectively, it was confirmed by computer simulations that the equalizer was updated effectively.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.604-615
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• 2019

Single-user spectrum sensing is susceptible to multipath effects, shadow effects, hidden terminals and other unfavorable factors, leading to misjudgment of perceived results. In order to increase the detection accuracy and reduce spectrum sensing cost, we propose an adaptive cooperative sensing strategy based on an estimated signal-to-noise ratio (SNR). Which can adaptive select different sensing strategy during the local sensing phase. When the estimated SNR is higher than the selection threshold, adaptive double threshold energy detector (ED) is implemented, otherwise cyclostationary feature detector is performed. Due to the fact that only a better sensing strategy is implemented in a period, the detection accuracy is improved under the condition of low SNR with low complexity. The local sensing node transmits the perceived results through the control channel to the fusion center (FC), and uses voting rule to make the hard decision. Thus the transmission bandwidth is effectively saved. Simulation results show that the proposed scheme can effectively improve the system detection probability, shorten the average sensing time, and has better robustness without largely increasing the costs of sensing system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4C
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• pp.217-225
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• 2011

In this paper, we propose an adaptive de-interlacing algorithm that is based on the degree of local complexity. The conventional intra field de-interlacing algorithms show the different performance according to the ways which find the edge direction. Furthermore, FDD (Fine Directional De-interlacing) algorithm has the better performance than other algorithms but the computational complexity of FDD algorithm is too high. In order to alleviate these problems, the proposed algorithm selects the most efficient de-interacing algorithm among LA (Line Average), MELA (Modified Edge-based Line Average), and LCID (Low-Complexity Interpolation Method for De-interlacing) algorithms which have low complexity and good performance. The proposed algorithm is trained by the DoLC (Degree of Local Complexity) for selection of the algorithms mentioned above. Simulation results show that the proposed algorithm not only has the low complexity but also performs better objective and subjective image quality performances compared with the conventional intra-field methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11B
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• pp.673-684
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• 2007

In this paper, we introduce an FARNS (Flooding algorithm with Adaptive Retransmission Nodes Selection). It is an efficient cross layer-based flooding technique to solve broadcast storm problem that is produced by simple flooding of nodes in wireless sensor network. FARNS can decrease waste of unnecessary energy by preventing retransmission action of whole network node by deciding retransmission candidate nodes that are selected by identification in MAC and distance with neighborhood node through received signal strength information in PHY. In simulation part, we show the results that FARNS has excellent performance than the other flooding schemes in terms of broadcast forwarding ratio, broadcast delivery ratio, number of redundancy packets and overhead. And FARNS can adjust of node ratio for retransmission operation, it can solve broadcast storm problem as well as meet the requirements of various network environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.647-669
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• 2016

Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.2
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• pp.37-44
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• 2014

The most effective method to overcome GPS jamming problem is to use an adaptive array antenna which has the capability of beamforming or nulling to a certain direction. In this paper, Space Time Adaptive Processing (STAP) beamforming algorithm of four elements array antenna will be designed and the anti-jamming performance will be analyzed. According to the analysis, the signal to noise ratio (SNR) and anti-jamming performance can be enhanced by beamforming algorithm. Also, the time tap effect of STAP algorithm will be analyzed theoretically and verified with array antenna modeling and simulation. Specially, the cautious selection of reference time tap in STAP can prevent the degradation of position accuracy performance.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.199-202
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• 2009

This paper proposes a novel adaptive algorithm for deinterlacing. In the proposed algorithm, the previously developed Enhanced ELA [6], Chen [9] and Li [10] algorithms were used as a basis. The fundamental mechanism was the selection and application of the appropriate algorithm according to the correlation with the previous and next field using temporal information. Extensive simulations were conducted for video sequences and showed good performance in terms of peak signal-to-ratio (PSNR) and subjective quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4573-4584
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• 2015

The traditional feature extraction algorithms for recognition of communication signals can hardly realize the balance between computational complexity and signals' interclass gathered degrees. They can hardly achieve high recognition rate at low SNR conditions. To solve this problem, a novel feature extraction algorithm based on Holder coefficient was proposed, which has the advantages of low computational complexity and good interclass gathered degree even at low SNR conditions. In this research, the selection methods of parameters and distribution properties of the extracted features regarding Holder coefficient theory were firstly explored, and then interval gray relation algorithm with improved adaptive weight was adopted to verify the effectiveness of the extracted features. Compared with traditional algorithms, the proposed algorithm can more accurately recognize signals at low SNR conditions. Simulation results show that Holder coefficient based features are stable and have good interclass gathered degree, and interval gray relation classifier with adaptive weight can achieve the recognition rate up to 87% even at the SNR of -5dB.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.3
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• pp.73-82
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• 1996

Vehicle movement detection by high order correlation analysis of optical sensor array signals is introduced. The optical sensors observe the road which is assumed to be a non-uniform speckle-like texture. The measurement system is applicable to general robotic movement detection because : 1) It employs a non-contact measurement method, 2) The system can be made very compact, and 3) It enables approximation of the movement trace with a sequence of arcs instead of the conventional connection of simple line segments. In this work, we have looked into estimation of running trace of an autonomous vehicle by observing the ground pattern.